Population and Society - Sustainability Indicators
Document prepared for SIMO
July 2001
Saviour Formosa
Section 1:
Introduction: Meaning of Sustainability Indicators
Population and its direct implications on Society and the Social Fabric incorporate one of the
fundamental issues that impinge any sustainable development issue. It is seen as the basis for any
sustainability study in human intervention both through its direct and indirect impacts. United Nations’
Agenda 21 identifies population growth as one of the crucial elements affecting long-term
sustainabilityi.
Population and its physical distribution has been seen by such initiatives (UN, OECD and Blue Plan),
as the main capital element comprising resource take-up. In fact, it is seen as the dynamic factor
affecting any type of environmental pressure due to its inherent nature, being the immediate provision
of basic needs to support itself. Populations are in themselves living entities and their survival depends
on the availability of immediate resources and sustaining those same resources.
Demographic change is synonymous with its impact on a country’s capacity on a wide range of
economic, social, cultural and environmental issues. Its fluctuations are dependant on a number of
variables such as fertility and mortality rates, attractiveness for migrants, and other related issues such
as health. Other issues having a direct change on the demographic status of a country include family
size, perceptions on contraception, movements towards individualistic norms, such as single person
households, amongst others.
Each of these issues places a strain on resources and may prove unsustainable, particularly where rapid
changes in both population growth and loss occurs in conjunction with poverty and lack of access to
resources. This is compounded by unsustainable patterns ranging from excessive production and
consumption scenarios. In addition, rapid changes on infrastructure such as rural abandonment in
favour of city life on one hand and depopulation of city cores outcomes which leave dying cities in its
wake, as exemplified by rust-belt cities and urban core neglect.
In view of this, the different impacts that these changes are having on society needs to be analysed also
in terms of other ’negative’ pressures on the environment such as resource consumption, effluent
generation and waste generated as well as the more visible issues such as settlement expansion, loss of
agricultural land and a rapidly shrinking countryside.
Due to the fact that most populations have taken up a sedentary way of life, divorcing themselves from
the nomadic lifestyles, the dependency on the immediate surroundings has grown exponentially, with
successive waves of social, cultural and technological advances. Intra-country and international
transactions have helped eased some of the strains on local resources but have generated myriad other
problems such as waste generation and increased in-migration. These latter-day situations have caused
high rates of population growth in the urban areas and depopulation in the rural areas. This has caused
an upheaval in the former land-use issues leading to rapid urban growth in conjunction with extreme
population densities.
These changes have caused a number of upheavals such as the need for energy materials, transportation
infrastructures, the construction of schools and hospitals, employment provision and education. Thus, it
is imperative that population studies are seen in line with other indicators, rather than in isolation, since
there are close linkages between population change and other demographic and social indicators, as
well as all indicators expressed in per capita terms (for example, GDP per capita). Population growth
usually has implications for indicators related to education, infrastructure, employment, including the
provision of housing, community facilities (education, health and social services), and utilities, the
management of traffic and communications, leisure and recreational needs and the quality of the urban
and environmental fabric. In view of this, population indicators are seen as directly related to human
settlements and the use of natural resources.
This document looks at sustainability in relation to population, society and settlements and refers to
Blue Plan/MAP, OECD and UN Agenda 21 Sustainability Indictors for the production of a list of
indicators that need to be analysed in the local context.
Maltese Situation
Population
The Maltese Islands comprise a complex issue when demographic studies are carried out. Due to their
extremely small size and very high population density, the impact on the relative indicators requires indepth studies. Malta ranks as the second-most dense country in the world, second only to Singapore
With over 1,200 persons per square kilometre, this density varies over the regions making up the
islands as well as between the islands themselves, with low densities in Gozo and Comino and a high
density in Malta.
This issue is compounded by the fact that regional densities are fluctuating in that the Grand Harbour
Local Plan Area has been continuously losing population since the early 1950s and is expected to
follow this trend unless drastic action to do otherwise is taken. However, some areas within the Grand
Harbour still have the highest density rates in Malta, with Senglea registering 22,000 persons per
square kilometre, though down from a 48,000 persons per square kilometre in 1931 ii.
The immediate repercussions on the social and physical fabric of the areas are immediately apparent,
with gross depopulation in the old areas, increasing number of vacant dwellings, high crime rates,
migration to as yet pristine areas and loss of the community soul of the towns in question.
Source: Census of Malta 1995 Web-Mapping Project: http://CensusofMalta1995
As per demographic structure, the Maltese Islands have been experiencing low birth and mortality rates
for some time, a situation that is characteristically late transitional in character. In the near future, it is
expected to reach a post-transitional stage, in which natural increase will be either very low or zero.
This means that population change will not be very large but may reach replacement ratios that would
create sustainable issues in themselves, such as the lack of working age cohorts, and an increase in
resource consumption of a very specific nature due to a rapid increase in the elderly component.
Life expectancy is anticipated to rise further, at a relatively faster rate for males than for females.
Fertility rates are expected to fluctuate slightly in the till 2005, and later on increase till 2020.
Migration will remain a volatile component of population change. International migration in the
Maltese islands is based on returning migrants and a small number of emigrants, with an average
annual positive migration component of 700 persons. On the other hand, internal migration is the main
component of change in the regional population studies. Studies on internal migration based on WSCiii
data and Census figuresiv indicate and that internal migration pivots around a preference to move
primarily within the town of origin, then to neighbouring towns and lastly to other regions, though the
nearest regions are still preferred. Thus, projections for future movements may to a certain extent be
predictable, but there are also unpredictable factors such as economic prospects, the state of the
environment, the quality of the urban fabric, and availability of housing that may impinge on the
changes.
The Maltese population is expected to increase to 434,000 by 2020 at an average increase of 2,300
persons per year, from a base population of 378,132 in 1995. This increase will place further pressures
on the socio-economic and socio-cultural structures in the Maltese Islands mainly due to the following
factorsv:
1.
2.
3.
4.
5.
6.
7.
8.
A larger population: From 378,132 in 1995, to 434,260 in 2020
A higher proportion of males:females, from a ratio of 97:100 in 1995, to 100:100, in
2020
A higher proportion of persons aged over 60 years: from 16 per cent in 1995, to 25
per cent in 2020 as well as an increase in the 80+ year component
A slightly lower birth rate: from 12.5 per 1,000 in 1995, to 12.3 per 1,000 in 2020
(rising between 1995 and 2010, then falling again)
A higher death rate: from 7.8 per 1,000 in 1995, to 9.8 per 1,000 in 2020, mainly due
to the higher number of elderly persons
A higher fertility rate: from 1.81 in 1995, to 1.97 in 2020, though still below
replacement levels, indicating a dying out population should these trends be sustained
for a number of decades
A higher life expectancy for males: from 74.9 years in 1995, to 76.5 in 2020 and a
marginally higher life expectancy for females: from 80.25 years in 1995, to 81.5 in
2020
An assumed average international migration of 775 in 2020, as opposed to 600 in
1995
Households
Household structure in Malta has been undergoing changes particularly during recent years where
changes in lifestyle have caused a decline in household size and in turn an increased related request for
dwellings. Malta is expected to experience an increase in 40,000 households from the 1995 Census
figures to 2020.
The main factors that are expected to cause this change include an increased female independence,
continued secularisation of Maltese society and a greater number of separations/divorces that all
contribute to an increase in the number of households. In addition, single parents, particularly mothers,
“are also increasing for a number of reasons including unplanned pregnancies, as well as planned
pregnancies by single females. Single motherhood tends to occur either among young females or
among older economically independent females seeking motherhood” vi.
These factors will have a direct impact of the need for smaller residences, as well as a diversified
housing market. The islands has a major stock of available units that are currently vacant and could
accommodate these new households. In addition, there needs to be a mentality change for persons to
purchase and sell of dwellings in relation to changes within their household structure, moving from
small to larger units and eventually to small units. The current use of dwelling results in diverse
problems relating to consumption patterns: energy consumption for the heating of large homes in
winter, deterioration of the stock and unavailability of stock for younger families.
The elderly make up a very high percentage of the Maltese population (16% as at 1995) and are
expected to increase to 25% in 2020. This factor that will contribute to an increase in the number of
smaller households and may be brought to fulfilment by government policy encouraging family care
for the elderly. Studies conducted locally show that 80 per cent of the Maltese elderly prefer to live at
home (Delia, 1993), thus increasing the need for more suitable dwellings.
The forecasts indicate that the Maltese Islands will experience the following factors vii:
1.
2.
3.
4.
A smaller household size: from 3.1 in 1995 to 2.7 in 2020
More households: from 119,479 in 1995 to 159,926 in 2020
More persons in institutions: from 4,087 in 1995 to 8,747 in 2020
A large percentage of under-utilised houses unless dwelling size fits household size
Settlement
Whilst the percentage of built-up land has increased from 4% in 1956 to 22% in 1997, this has been
compounded by the fact that the rate of land take-up for dwelling purposes is higher than the demand.
For a demand of an average of 2,500 new dwellings per year an average of 4,000 units are being
developed during the same period. This, together with antiquated rent laws and a high rate of
speculation has resulted in a vacant dwelling stock of 35,723 as at 1995, inclusive of summer homes.
The land available for future dwelling stock is being rapidly taken-up at an alarming rate, thus further
straining the Temporary Provision Schemes as outlined in 1988.
At the same time, cities like Valletta, Floriana, and Cottonera are rapidly losing their population and
increasing their vacant stock.
In view of the above, the need for indicators identifying the need for analysis is being listed below.
Each indicator relates to the demographic and social situation of the Maltese Islands.
Section 2:
List of Population and Society Sustainability Indicators
This section looks at the indicators as identified by the OECD, MAP/Blue Plan and the UN.
Whilst the MAP/Blue Plan and the UN outline specific Indicators as listed below, the OECD tend to
look at the social aspect as an add-on to their environmental performance indicators. This was indicated
by “emphasising that the three dimensions of sustainable development - economic, environmental, and
social – should be reflected in the set of OECD indicators, and that in general, further attention has to
be dedicated to the social aspect of sustainable development. Several issues such as tourism, urban
environmental quality, transport, sewage treatment, and energy efficiency in buildings, were identified
by delegates as possible candidate areas for further study”viii.
On the other hand, both the Blue Plan and UN initiatives have looked at the social aspects in context, as
outlined below.
MAP/Blue: Plan indicators and methodology
The Blue Planix adopted a list of 130 indicators based on a system of 3 categories of the PSR Model
(Pressures, State and Responses). This methodology was based on an outline of 119 indicators that are
quantitative in nature and can be computed whilst there are also 11 qualitative indicators. The
categorisation relating to this paper is based on the following:
Population and Society
Demography and population
Standard of life, social inequalities, poverty, employment, unemployment
Culture, education, training, public awareness
Health, public health
Consumption and production patterns
Territory and Human Settlements
Habitat and urban systems
The chosen indicators that relate to the topic under review include 6 Pressure, 10 State and 5 Response
issues.
THEME
PRESSURE
STATE
RESPONSE
1 POPULATION AND SOCIETY
1.1 DEMOGRAPHY AND
1. Population growth rate
2. Total fertility rate
POPULATION
1.2 STANDARD OF LIFE,
EMPLOYMENT, SOCIAL
INEQUITIES, POVERTY,
UNEMPLOYMENT
1.3 CULTURE, EDUCATION,
TRAINING, AWARENESS
6. School enrolment gross
ratio
IMPROVEMENT
1.4 HEALTH, PUBLIC HEALTH
1.5 CONSUMPTION AND
PRODUCTION PATTERNS
3. Women per hundred men
in the labour force
4. Human poverty index
(HPI)
7. Difference between male
and female school enrolment
ratios
8. Production of cultural
goods
11. Life expectancy at birth
14. Annual energy
consumption per inhabitant
15. Number of passengers
cars per 100 inhabitants
5. Employment rate
9. Share of private and
public finances allocated to
the professional training
10. Public expenditure for
the conservation and value
enhancement of natural,
cultural and historical
heritage
13. Access to safe drinking
water
12. Infant mortality rate
16. Main telephones lines per
100 inhabitants
17. Distribution of food
consumption per income
decile
2 LANDS AND AREAS
2.1 HABITAT AND URBAN
SYSTEM
18. Urban population
20. Urbanisation rate
growth rate
19. Loss of agricultural land 21. Floor area per person
due to urbanisation
UN: indicators and methodology
Another set of indicators reviewed for the Population and Society Topic are extracted from the UN
Indicators for Social Aspects of Sustainable Development. The following list is based on their
respective Chapters from the document “Indicators Of Sustainable Development: Framework And
Methodologies”x.
Their system of information creation was based on the use of a series of methodology sheets as
presented in Background Paper no. 15, at the fourth session of the UN Commission on Sustainable
Development, in April/May 1996. Since then additional and revised methodology sheets have been
submitted by the lead agencies and were incorporated into the revised edition of the document. In a few
instances, methodology sheets are still being developed and in these cases, a "bookmark" has been
included, stating the name of the indicator, a brief definition, the unit of measurement, and its
placement in the framework. An annex of these sheets is being included with this document in order to
serve as guidance material for the entities responsible for the data-gathering process.
The list of population and Society Indicators is listed below:
Combating poverty






Unemployment rate
Head count index of poverty
Poverty gap index
Squared poverty gap index
Gini index of income inequality
Ratio of average female wage to male wage
Demographic dynamics and sustainability




Population growth rate
Net migration rate
Total fertility rate
Population density
Promoting education, public awareness and training











Rate of change of school-age population
Primary school enrolment ratio--gross
Primary school enrolment ratio--net
Secondary school enrolment ratio--gross
Secondary school enrolment ratio--net
Adult literacy rate
Children reaching grade 5 of primary education
School life expectancy
Difference between male and female school enrolment ratios
Women per hundred men in the labour force
GDP spent on education
Protecting and promoting human health












Basic sanitation: percent of population with adequate excreta disposal facilities
Access to safe drinking water
Life expectancy at birth
Adequate birth weight
Infant mortality rate
Maternal mortality rate
Nutritional status of children
Immunization against infectious childhood diseases
Contraceptive prevalence
Proportion of potentially hazardous chemicals monitored in food
National health expenditure devoted to local health care
Total national health expenditure related to GNP
Promoting sustainable human settlement development





Rate of growth of urban population
Per capita consumption of fossil fuel by motor vehicle transport
Human and economic loss due to natural disasters
Percent of population in urban areas
Area and population of urban formal and informal settlements



Floor area per person
House price to income ratio
Infrastructure expenditure per capita
There are overlapping indicators between these 2 lists, with the UN list being more exhaustive. To this
effect, an exercise has been carried out whereby the two list have been integrated and some indicators
that are not relative to the Maltese context or are too complex to work out, have been omitted.
Section 3:
Proposals on which Population and Society Sustainability Indicators are
suitable for Malta
In view of the particular situation of the Maltese Islands, the indicators that could be taken from both
the Blue Plan and UN lists have been identified and are listed below:
Standard of Life, Employment, Social Inequities, Poverty, Unemployment
Employment rate
Head count index of poverty
Poverty gap index
Ratio of average female wage to male wage
Women per hundred men in the labour force
Demography and Population
Population growth rate
Net migration rate
Total fertility rate
Population density
Ageing growth rate
Culture, Education, Training, Awareness Improvement
Rate of change of school-age population
Primary school enrolment ratio--gross
Secondary school enrolment ratio--gross
Adult literacy rate
Difference between male and female school enrolment ratios
GDP spent on education
Production of cultural goods
Share of private and public finances allocated to the professional training
Public expenditure for the conservation and value enhancement of natural, cultural and historical heritage
Health
Basic sanitation: percent of population with adequate excreta disposal facilities
Access to safe drinking water
Life expectancy at birth
Infant mortality rate
Contraceptive prevalence
National health expenditure devoted to local health care
Total national health expenditure related to GNP
Urban System
Rate of growth of urban population
Urbanisation rate
Per capita consumption of fossil fuel by motor vehicle transport
Area and population of urban formal and informal settlements
Loss of agricultural land due to urbanisation
Floor area per person
House price to income ratio
Annual energy consumption per inhabitant
Number of passengers cars per 100 inhabitants
Main telephones lines per 100 inhabitants
Main personal computers per 100 inhabitants
Distribution of food consumption per income decile
Section 4:
Classification of indicators as per ease of data mining for analysis processes
This section gives an outline of the indicators chosen, the computation parameters, the data
creators/custodians and comments as necessary. 3 indicators have been added over and above the listed
Blue Plan and UN indicators, as they were seen to be more indicative of the situation on Malta: mainly
Ageing growth rate, Dwelling density and Vacant dwellings. These indicators should reflect the
expected changes as well as identify a holistic approach to the solution of a number of demographic
and social issues.
Refer to document UN Blue Plan List Demog.xls attached
Section 5:
Executive Summary
Population and its direct implications on Society and the Social Fabric is considered to be the basis on
which any sustainability study in human intervention builds upon as it is one of the crucial elements
affecting long-term sustainability. Demographic change is synonymous with its impact on a country’s
capacity on a wide range of economic, social, cultural and environmental issues and its fluctuations are
dependant on a number of variables such as fertility and mortality rates, attractiveness for migrants, and
other related issues such as health.
The Maltese Islands comprise a complex issue when demographic studies are carried out, mainly due to
its small size and very high population density. Demographic studies form the basis for related issues
such as housing, transport, employment, consumption, each of which require analysis on the impact of
demographic change.
The Maltese population is expected to increase to 434,000 by 2020 at an average increase of 2,300
persons per year, from a base population of 378,132 in 1995.
Household structure in Malta has been undergoing changes particularly during recent years where
changes in lifestyle have caused a decline in household size and in turn the related request for
dwellings. Malta is expected to experience an increase in 40,000 households from the 1995 Census
figures to 2020.
Whilst the percentage of built-up land has increased from 4% in 1956 to 22% in 1997, this has been
compounded by the fact that the rate of land take-up for dwelling purposes is higher than the demand.
Whereas annual demand averages 2,500 new dwellings, on average 4,000 units are being developed
during the same period, resulting in an ever-increasing vacant dwelling stock that stood at 35,723 in
1995, inclusive of summer homes.
Data Sources
Comments on
computations
Impossible to compute
Very difficult to
compute
Somewhat difficult to
compute
Easily Computed
Indicator
Standard of life, employment, social inequities, poverty,
unemployment
Employment rate
Head count index of poverty
Poverty gap index
Ratio of average female wage to male wage
Women per hundred men in the labour force
ETC, NSO, PA
NSO
NSO
ETC, NSO
ETC, NSO, PA
Demography and Population
Population growth rate
NSO, PA
Net migration rate
Total fertility rate
Population density
NSO, PA
NSO, PA
NSO, PA
Ageing growth rate
NSO, PA
Culture, education, training, awareness improvement
Rate of change of school-age population
Primary school enrolment ratio--gross
Secondary school enrolment ratio--gross
Adult literacy rate
Difference between male and female school enrolment ratios
GDP spent on education
Production of cultural goods
Share of private and public finances allocated to the
professional training
Public expenditure for the conservation and value enhancement
of natural, cultural and historical heritage
NSO, Education
Department
NSO, Education
Department
NSO, Education
Department
NSO, Education
Department
NSO, Education
Department
NSO, Education
Department
NSO, Education
Ministry
NSO, Education
Department
NSO, Education
Ministry, Museums
Department
Health
Total national health expenditure related to GNP
WSC, NSO, Health
Ministry, Health
Department
WSC, NSO, Health
Ministry, Health
Department
NSO, PA
NSO
NSO, Health Ministry,
Health Department
NSO, Health Ministry,
Health Department
NSO, Health Ministry,
Health Department
Rate of growth of urban population
PA
Basic sanitation: percent of population with adequate excreta
disposal facilities
Access to safe drinking water
Life expectancy at birth
Infant mortality rate
Contraceptive prevalence
National health expenditure devoted to local health care
Urban
System
Indicator
specific to
Malta
Urbanisation rate
Per capita consumption of fossil fuel by motor vehicle transport
Area and population of urban formal and informal settlements
Loss of agricultural land due to urbanisation
Floor area per person
House price to income ratio
PA
NSO, PA, Enemalta
PA
NSO, PA, Agriculture
Department
NSO, PA
NSO, PA, Estate
Agents, Housing
Ministry
Dwelling density
PA
Vacant dwellings
Annual energy consumption per inhabitant
Main telephones lines per 100 inhabitants
Main personal computers per 100 inhabitants
NSO, PA
NSO, PA, Enemalta
NSO, PA, Transport
Ministry
NSO, Maltacom.
Vodafone
NSO
Distribution of food consumption per income decile
NSO
Number of passengers cars per 100 inhabitants
Out-migration from the old cities and towns such as Valletta, Floriana, and Cottonera is increasing the
vacant stock component, aiding the deterioration of the dwelling stock and in turn leaving behind a
disrupted social structure.
This study has identified a number of indicators that would help in the monitoring of the demographic
and social fabric of the Maltese Islands. These are categorised as follows:





Standard of life, employment, social inequities, poverty, unemployment
Demography and Population
Culture, education, training, awareness improvement
Health
Urban System
Dated: 01 July 2001
Saviour Formosa
5 Indicators
5 Indicators
9 Indicators
7 Indicators
14 Indicators
Indicator
specific to
Malta
Indicator
specific to
Malta
Annex
Demography and Society Sustainability Indicators:
Document extracted from the UN Sustainability website at:
http://www.un.org/esa/sustdev/agenda21.htm
Chapter 3: Combating poverty






Unemployment rate
Head count index of poverty
Poverty gap index
Squared poverty gap index
Gini index of income inequality
Ratio of average female wage to male wage
Chapter 3: Combating poverty
UNEMPLOYMENT RATE
Social
Chapter 3
Driving Force
1. Indicator
(a)
Name:
Unemployment
rate.
(b) Brief Definition: Unemployment rate is the ratio of unemployed people to the labour force.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
(b) Type of Indicator: Driving Force.
Chapter
3:
Combating
Poverty.
3. Significance (Policy Relevance)
(a) Purpose: The unemployment rate measures the part of the labour force which, during the survey
reference period, was neither (i) at work nor temporarily absent from work (i.e. not in paid or selfemployment); (ii) available for work; or (iii) seeking work.
(b) Relevance to Sustainable/Unsustainable Development: Unemployment is useful and relevant to
measuring sustainable development, especially if uniformly measured over time, and considered with
other socioeconomic indicators. It is one of the main reasons for poverty in rich and medium income
countries and among persons with high education in low income countries (no work, no income but
compensation from insurance schemes or other welfare state systems whenever they exist). It should
be noted, however, that it is common to find people working full-time but remaining poor due to the
particular social conditions and type of industrial relations prevalent in their country, industry, or
occupation.
(c) Linkages to Other Indicators: This indicator is linked to other socioeconomic indicators such as
poverty measures and adult literacy.
(d) Targets: National targets for unemployment are common.
(e) International Conventions and Agreements: See 7 iii below.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The definitions for labour force, employed population, and
unemployed population are well established by international agreements (see section 7 below).
i) Labour Force: The current economically active population or labour force has two components: the
employed and the unemployed population. The international standard definition of labour force
established by the Thirteen International Conference of Labour Statisticians (ILO, 1982) is based on the
following elements:
--The survey population: All usual residents (de jure population) or all persons present in the country at
the time of the survey (de facto population). Some particular groups, such as the armed forces or other
populations living in institutions, nomadic people, etc. may be excluded.
--An age limit: In countries where compulsory schooling and legislation on the minimum age for
admission to employment have broad coverage and are widely respected, the age specified in these
regulations may be used as a basis for determining an appropriate minimum age limit for measuring the
economically active population.
In other countries the minimum age limit should be determined empirically on the basis of (i) the extent
and intensity of participation in economic activities by young people, and (ii) the feasibility and cost of
measuring such participation with acceptable accuracy. Some countries also determine a maximum age
for inclusion in the labour force.
--The involvement in economic activities during the survey reference period: The concept of economic
activity adopted by the Thirteenth International Conference of Labour Statisticians (1982) is defined in
terms of production of goods and services as set forth by the United Nations System of National
Accounts, (revised in 1993).
-- A short reference period: For example, one week or a day.
ii) Employed population: According to the 1982 international definition of employment (ILO, 1983) the
employed comprise all persons above the age specified for measuring the labour force, who were in the
following categories:
--Paid employment: (i) at work: persons who, during the reference period, performed some work (at
least one hour) for wage or salary, in cash or in kind; (ii) with a job but not at work: persons who, having
already worked in their present job, were temporarily not at work during the reference period but had a
formal attachment to their job;
--self-employment: (i) at work: persons who, during the reference period, performed some work (at least
one hour) for profit or family gain, in cash or in kind; (ii) with an enterprise but not at work : persons with
an enterprise, which may be a business enterprise, a farm or a service undertaking, who were
temporarily not at work during the reference period for some specific reason.
iii) Unemployed population: According to the 1982 international definition of employment (ILO, 1983) the
unemployed comprise all persons above the age specified for measuring the labour force, who during
the survey reference period were at the same time: (i) not in paid employment or self-employment, not
even for an hour; (ii) available for work; and (iii) seeking work.
(b) Measurement Methods:
--Sources may be grouped into two broad categories: (i) population censuses and household sample
surveys; and (ii) various types of administrative records, such as employment exchange registers,
unemployment insurance records or social security files, which cover different segments of the target
population (numerator of the indicator) through different conceptual frameworks.
Estimates according to the international standards can in practice be made most reliably on the basis of
data collected through household surveys and population censuses. Some of the criteria specified in the
international standards can only be implemented precisely through personal interviews. This is the only
data source which, on a regular basis and with an appropriate survey design, can cover virtually the
entire population of a country, all branches of economic activity, sectors of the economy, types of activity
status and categories of workers and which allow joint, mutually exclusive measurement of the
employed, unemployed and economically inactive.
--The one hour criterion is necessary to cover all regular and irregular types of employment that may
exist in a given country; to have the total employment corresponding to aggregate production; and to
justify the international definition of unemployment as a total lack of work, so that the two components of
the labour force are mutually exclusive categories.
--Temporary absence from work is a notion which refers to situations in which a period of work is
interrupted by a period of absence, i.e. persons have already worked at their current activity and are
expected to return to their work after the period of absence.
For paid employment, temporary absence from work is ascertained on the basis of the concept of formal
job attachment according to one or more of the following criteria: continued receipt of wage or salary; an
assurance of a return to work following the end of the contingency, or an agreement as to the date of
return; the elapsed duration of absence from the job which, wherever relevant, may be that duration for
which workers can receive compensation benefits without obligation to accept other jobs.
For self-employment, the concept of temporary absence from work is based on two criteria: the
continued existence of the enterprise and the duration of absence.
--Availability for work means that, given a work opportunity, a person should be able and ready to work
during the survey reference period. In practice, many countries prefer to use a slightly longer reference
period for availability (not everyone who is seeking work can be expected to take up a job immediately
one is offered).
--Seeking work means having taken specific active steps in a specified recent period to seek paid
employment or self-employment. This specified period may be longer than the survey reference period
(e.g. one month or the four weeks before it) to take account of the time-lags which often follow initial
steps to obtain work, and during which jobseekers may not take any other initiatives to find work.
The 1982 international standards introduced a provision which allows for the relaxation of the seeking
work criterion in situations where the conventional means of seeking work are of limited relevance,
where the labour market is largely unorganised or of limited scope, where labour absorption is at the
time inadequate, or where the labour force is largely self-employed .
--Particular groups: (i) Future starts i.e. persons who have made arrangements to take up paid
employment or to undertake self-employment activity at a date subsequent to the reference period, if
currently available for work, are to be considered as unemployed whether or not they continue to seek
work. (ii) Lay-offs without formal job attachment but seeking and currently available for work are to be
classified as unemployed. (iii) Students seeking and available for work are unemployed (the availability
of full-time students seeking full-time work, however, may be questionable). (iv) Persons seeking and
available for apprenticeship are to be classified as unemployed if the apprenticeship is an economic
activity in the sense of SNA. (v) Beneficiaries of employment creation schemes are unemployed if the
training does not take place within the context of an enterprise nor is associated with the productive
activities of the enterprise, and no formal job attachment exists; but there is a definite commitment to
employment after the end of the training.
(c) The Indicator in the DSR Framework: In the DSR framework the unemployment rate (%) has been
put into the Driving Force indicators category.
(d) Limitations of the Indicator: The concept of poverty refers to a long lasting situation while the
number of unemployed can change very fast depending of various short term circumstances. Therefore,
it may be interesting to use the concept of usual unemployment and usual economically active
population instead of current unemployment and labour force. The difference is that the survey
reference period is a long one (e.g. one year) and that a person is to be classified in one category
(employed, unemployed or inactive) according to the category in which he or she is classifiable for the
greatest amount of time.
National capacity to collect data related to unemployment varies considerably. There are often severe
problems with data quality. In addition, the informal sector, and unpaid labour in, for example,
households and the agricultural sector are not captured by this indicator.
(e) Alternative Definitions: The unemployment rate is more meaningful when shown by age, sex and
other relevant variables such as the educational level, previous work experience etc.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Labour force (total number of persons) and total number of
unemployed persons, derived from the same survey.
(b) Data Availability: The availability of the rate of unemployment in recent years (1992, 1993 or 1994)
is ascertained for 80 countries. The sources are labour force surveys or general household surveys for
57 countries (3 do not give the distribution by gender; 15 also use employment office statistics of which
13 provide the distribution by gender); employment office statistics exclusively for 18 countries (5 do not
give the distribution by gender); and official estimates for 4 countries (3 give the distribution by gender).
(c) Data Sources: See section 7i below.
6. Agencies Involved in the Development of the Indicator
The lead agency involved is the International Labour Office (ILO) of the United Nations, located in
Geneva. The contact point is the Focal Point for Environment and Sustainable Development, ILO; fax
no. (41-22) 798 8685.
7. Further Information
(a) Data:
Yearbook of Labour Statistics, ILO, Geneva;
Bulletin of Labour Statistics (quarterly) and its Supplement (January/February, April/May, July/August
and October/November), ILO, Geneva;
Statistical yearbooks and other publications issued by the national statistical offices.
(b) Methodology:
Surveys of Economically Active Population, Employment, Unemployment and Underemployment -An
ILO Manual on Concepts and Methods, ILO, Geneva, 1992.
Sources and Methods: Labour Statistics, Volumes 3 and 5, ILO, Geneva, 1991 and 1990, currently
updated.
System of National Accounts 1993, Commission of the European Communities, International Monetary
Fund, Organisation for Economic Co-operation and Development, United Nations, World Bank,
Brussels/Luxembourg, New York, Paris, Washington, D.C., 1993;
Current international recommendations on labour statistics, ILO, Geneva, 1988. See particularly the
Resolution Concerning Statistics of the Economically Active Population, Employment, Unemployment
and Underemployment, adopted by the Thirteenth International Conference of Labour Statisticians
(October 1982).
(c) International Conventions and Recommendations:
Labour Statistics Convention (No. 160) and Recommendation (No. 170), 1985.
HEAD COUNT INDEX OF POVERTY
Social
Chapter 3
State
1. Indicator
(a) Name: Head Count Index of Poverty.
(b) Brief Definition: The proportion of the population with a standard of living below the poverty line.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 3: Combating Poverty.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: The most important purpose of a poverty measure is to enable poverty comparisons.
These are required for an overall assessment of a country's progress in poverty alleviation and/or the
evaluation of specific policies or projects. An important case of a poverty comparison is the poverty
profile which shows how the aggregate poverty measure can be decomposed into poverty measures for
various sub-groups of the population, such as by region of residence, employment sector, education
level, or ethnic group. A good poverty profile can help reveal a number of aspects of poverty-reduction
policies, such as the regional or sectoral priorities for public spending. Poverty comparisons are also
made over time, in assessing overall performance from the point of view of the poor.
(b) Relevance to Sustainable/Unsustainable Development: Measures of poverty are a very
significant consideration of sustainable development. The eradication of poverty remains a major
challenge for policy decision makers. Furthermore, an integrative viewpoint which simultaneously takes
account of development issues, resource use and environmental quality, and human welfare must be
taken if sustainable progress is to be achieved.
The Head Count Index of poverty captures the prevalence of poverty by measuring the proportion of
population for whom consumption (or any other suitable measure of living standard) is below the poverty
line. An increase in this indicator implies a worsening of the poverty situation with a greater proportion of
the population falling below the poverty line.
(c) Linkages to Other Indicators: In general, this indicator is linked to many other sustainable
development measures, for example, net migration rate, adult literacy rate, Gross Domestic Product per
capita, and population living below the poverty line in dryland areas. In particular, the Head Count Index
is closely associated to the Poverty Gap Index and the Squared Poverty Gap Index which capture
successively more detailed aspects of the poverty situation. The Head Count Index measures how
widespread poverty is, the Poverty Gap Index measures how poor the poor are, and the Squared
Poverty Gap Index measures the severity of poverty by giving more weight to the poorest of the poor.
(d) Targets: Not available.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: A poverty measure is a summary statistic on the economic
welfare of the poor in a society. There is no one universally accepted single measure of poverty. A
number of different approaches exist (see, for example, the methodology sheets for the Poverty Gap
Index and the Squared Poverty Gap Index). This methodology sheet guides the reader along certain key
issues, such as the different approaches to measuring individual welfare, without prescribing decisions.
Consequently, it is directed at comparability over time within a given country, as it helps national
practitioners specify poverty indicators that match their specific situation and preferred approach.
However, this is at the expense of international comparability.
To compute poverty measures, the following questions related to identifying and defining the poor must
be addressed first:
i) How do we measure an individual's economic welfare?
ii) At what level of measured welfare is a person considered poor?
(b) Measurement Methods: The Head Count Index (H) is the proportion of the population whose
economic welfare (y) is less than the poverty line (z). If q people are deemed to be poor in a population
of size n then H=q/n. For computing the Head Count Index, estimates of individual economic welfare
and the poverty line are required.
i) Measuring Individual Welfare: There are a number of different approaches to measuring welfare. The
approaches differ in terms of the importance attached to the individual's own judgment of well-being
versus a concept of welfare decided upon by somebody else. The former would focus on measuring an
individual's consumption of a bundle of goods and services. An example of the latter would be defining
welfare by the level of nutritional intake, even though people do not live on food alone, or make food
choices solely on the basis of nutrition. Approaches in practice also differ according to how difficult it is
to obtain certain types of data in specific settings.
Typically one finds that poverty comparisons in developing countries put a high weight on nutritional
attainments, consistent with the behaviour of poor people in a specific society. A comprehensive
measure of consumption (for example, total expenditure on all goods and services consumed, including
non-market goods, such as consumption from a farmer's own product) has been more popular than
using current income in the development literature. This is due in part to the fact that incomes are harder
to measure accurately. Current consumption is also likely to give a better indication than current income
of a household's typical, long-term, economic welfare; income may fluctuate greatly over time,
particularly in rural economies (see Ravallion reference in section 7a below).
The following methods can be used for measuring individual standards of living:
--Consumption per equivalent male adult: Since households differ in size and composition, a simple
comparison of aggregate household consumption can be misleading about the welfare of individual
members of the household. Therefore, for any given household, an equivalence scale is used to
approximate the number of single adults, based on observed consumption behaviour. There are a
number of value judgments embedded in this practice; for example, differences in needs are reflected in
differences in consumption. Adult females and children are assigned a male equivalence of less than
one since they typically consume less; however, that may not mean that they have lower "needs" but
rather have less power within the household. The existence of size economies in consumption may also
mean that two people can live more cheaply together than apart (for a further discussion of these
issues, see Ravallion reference in section 7a below).
--Undernutrition: This is a distinct concept, although closely associated with poverty. Undernutrition can
be viewed as a specific type of poverty, namely food energy poverty. There are a number of arguments
for and against using this as a measure of well-being. A practical advantage is that this measure does
not have to be adjusted for inflation and would not be constrained by any inadequacy of price data.
Measures of child nutritional status can help capture aspects of welfare, such as distribution within the
household which are not adequately reflected in other indicators. However, nutrition is not the only
aspect that matters to the well-being of people, including the poor. Thus, poverty comparisons based
solely on nutrition alone may be limited and deceptive.
ii) Defining the Poverty Line: In practice, there are a number of alternative approaches to defining
poverty lines:
--Absolute poverty lines: An absolute poverty line is one which is fixed in terms of the living standard
indicator being used (consumption, nutrition). It is fixed over the entire domain of comparison, that is, a
poverty line which assures the same level of economic welfare would be used to measure and compare
poverty across provinces or different situations. The poverty line may still vary, but only so as to
measure the differences in the cost of a given level of welfare. Absolute poverty lines are more common
in developing country literature.
The most common approach to defining absolute poverty lines is to estimate the cost in each region or
at each date of a certain bundle of goods necessary to attain basic consumption needs (this is called the
basic needs approach). The most important component of basic needs is a recommended food energy
intake, supplemented by essential non-food goods. To measure food energy requirements, one needs
to make an assumption about activity levels which in turn determine energy requirements to maintain
the body's metabolic rate at rest. Once the food energy intake has been determined, and its cost has
been calculated, an allowance for non-food spending can be added by finding the total expenditure level
at which a person typically attains the food component of the poverty line. An alternative (lower)
allowance for non-food goods is to use the average non-food spending of people who can just afford the
food component of the poverty line: it can be argued that this is a reasonable lower bound for the nonfood component of the poverty line (see Ravallion reference in section 7a below).
--Relative poverty lines: These have dominated developed country literature where many studies have
used a poverty line which is set at, for example, 50% of the national mean income. When the poverty
line is fixed as a proportion of the national mean, if all incomes increase by the same proportion, there
would be no change in relative inequalities and the poverty line would simply increase by the same
proportion; that is, the poverty measure will not change. This can make such poverty lines deceptive for
some purposes, such as assessing whether poor people are better or worse off.
A cross-country comparison of 36 countries, both developed and developing, revealed that real poverty
lines will tend to increase with economic growth, but they will do so slowly for the poorest countries.
Therefore, the concept of absolute poverty appears to be more relevant to low income countries, while
relative poverty is of more relevance to high income countries.
(c) The Indicator in the DSR Framework: In the DSR Framework, this indicator represents a measure
of the State of poverty.
(d) Limitations of the Indicator: In practice, most applications in developing countries have used
consumption per person. This probably overstates the extent to which poverty is associated with larger
family sizes. But other aspects of the poverty profile (such as assessments of the regional or sectoral
poverty profiles) tend to be more robust as a measurement choice.
It is important to note that a certain amount of arbitrariness and value judgement are unavoidable in
defining individual welfare and any poverty line. Therefore, the overall assessment of the poverty
situation should pay particularly attention to how the choices made affect poverty comparisons, since
these are generally what matter most to policy implications. An increasingly common practice is to
recalculate the poverty measures using various poverty lines, and to test whether the qualitative poverty
comparisons are robust to the choice.
It should be noted that there are several comparability problems across countries in the use of data from
household surveys (see section 5 below). In addition, definitions of poverty are lacking in some
countries or vary from country to country. These problems are diminishing over time as survey
methodologies are improving and becoming more standardized, but they remain.
(e) Alternative Definitions: The Poverty Gap Index and the Squared Poverty Gap Index represent
alternative definitions for a poverty indicator (see section 3c above and the relevant methodology sheets
for these indicators).
5. Assessment of the Availability of Data from International and National Sources
The most important source of data on living standards is household surveys. The results of these
surveys can be obtained from government statistical agencies, often via published reports. About two
thirds of the developing countries have done sample household surveys which are representative
nationally, and some (but certainly not all) of these provide high-quality data on living standards.
Data can also be obtained from international agencies such as The World Bank (mostly data for low and
middle income countries emerging from the Living Standards Measurement Study and Social
Dimensions of Adjustment Project for Sub Saharan Africa). Data for developed countries can be
obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or
the Organisation for Economic Co-operation and Development (OECD).
6. Agencies Involved in the Development of the Indicator
The lead agency involved is The World Bank (WB). The contact point is the Chief, Indicators and
Environmental Valuation Unit, Environment Department, WB; fax no. (1-202) 477 0968.
7. Further Information
(a) Further Readings:
Ravallion, M. Poverty Comparisons. Fundamentals in Pure and Applied Economics, Volume 56,
Harwood Academic Press, Switzerland. 1994.
POVERTY GAP INDEX
Social
Chapter 3
State
1. Indicator
(a) Name: Poverty Gap Index.
(b) Brief Definition: The mean over the population of the proportionate poverty gap, where the poverty
gap is given by the distance of the poor below the poverty line, as a proportion of the line. The non-poor
are counted as having zero poverty gap.
(c) Unit of Measurement: Fraction bounded by 0 and the Head Count Index.
2. Placement in the Framework
(a) Agenda 21: Chapter 3: Combating Poverty.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: The most important purpose of a poverty measure is to enable poverty comparisons.
These are required for an overall assessment of a country's progress in poverty alleviation and/or the
evaluation of specific policies or projects. An important case of a poverty comparison is the poverty
profile which shows how the aggregate poverty measure can be decomposed into poverty measures for
various sub-groups of the population, such as by region of residence, employment sector, education
level, or ethnic group. A good poverty profile can help reveal a number of aspects of poverty-reduction
policies, such as the regional or sectoral priorities for public spending. Poverty comparisons are also
made over time, in assessing overall performance from the point of view of the poor.
(b) Relevance to Sustainable/Unsustainable Development: Measures of poverty are a very
significant consideration of sustainable development. The eradication of poverty remains a major
challenge for policy decision makers. Furthermore, an integrative viewpoint which simultaneously takes
account of development issues, resource use and environmental quality, and human welfare must be
taken if sustainable progress is to be achieved.
The Poverty Gap Index measures the depth of poverty in a country or region, based on the aggregate
poverty deficit of the poor relative to the poverty line. Since the Head Count Index (see section 3c
below) is not sensitive to changes in the status of those already below the poverty line, it is inadequate
in assessing the impact of specific policies on the poor. On the other hand, the Poverty Gap Index
increases with the distance of the poor below the poverty line, and thus gives a good indication of the
depth of poverty. A decline in the Poverty Gap Index reflects an improvement in the current situation.
(c) Linkages to Other Indicators: In general, this indicator is linked to many other sustainable
development measures, for example, net migration rate, adult literacy rate, Gross Domestic Product per
capita, and population living below the poverty line in dryland areas. More specifically, the poverty
measures discussed in this and two other methodology sheets; namely the Head Count Index, the
Poverty Gap Index, and the Squared Poverty Gap Index; capture successively more detailed aspects of
the poverty situation. The Head Count Index measures how widespread poverty is, the Poverty Gap
Index measures how poor the poor are, and the Squared Poverty Gap Index measures the severity of
poverty by giving more weight to the poorest of the poor.
(d) Targets: Not available.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: A poverty measure is a summary statistic on the economic
welfare of the poor in a society. There is no one universally accepted single measure of poverty. A
number of different approaches exist (see, for example, the methodology sheets for the Poverty Gap
Index and the Squared Poverty Gap Index). This methodology sheet guides the reader along certain key
issues, such as the different approaches to measuring individual welfare, without prescribing decisions.
Consequently, it is directed at comparability over time within a given country, as it helps national
practitioners specify poverty indicators that match their specific situation and preferred approach.
However, this is at the expense of international comparability.
To compute poverty measures, the following questions related to identifying and defining the poor must
be addressed first:
i) How do we measure an individual's economic welfare?
ii) At what level of measured welfare is a person considered poor?
(b) Measurement Methods: The Poverty Gap Index is the mean across the population of a household
poverty measure (weighted by household-size). The Index takes the value zero if the average economic
welfare (for example, consumption) is above the poverty line, and is measured by the function 1-y/z if it
is at or below the line, where z is the poverty line and y denotes the mean consumption of the poor. For
computing the Poverty Gap Index, estimates of individual economic welfare (y), and the poverty line (z)
are required.
i) Measuring Individual Welfare: There are a number of different approaches to measuring welfare. The
approaches differ in terms of the importance attached to the individual's own judgment of well-being
versus a concept of welfare decided upon by somebody else. The former would focus on measuring an
individual's consumption of a bundle of goods and services. An example of the latter would be defining
welfare by the level of nutritional intake, even though people do not live on food alone, or make food
choices solely on the basis of nutrition. Approaches in practice also differ according to how difficult it is
to obtain certain sorts of data in specific settings.
Typically one finds that poverty comparisons in developing countries put a high weight on nutritional
attainments, consistent with the behaviour of poor people in a specific society. A comprehensive
measure of consumption (for example, total expenditure on all goods and services consumed, including
non-market goods, such as consumption from a farmer's own product) has been more popular than
using current income in the development literature. This is due in part to the fact that incomes are harder
to measure accurately. Current consumption is also likely to give a better indication than current income
of a household's typical, long-term, economic welfare; income may fluctuate greatly over time,
particularly in rural economies (see Ravallion reference in section 7a below).
The following methods can be used for measuring individual standards of living:
--Consumption per equivalent male adult: Since households differ in size and composition, a simple
comparison of aggregate household consumption can be misleading about the welfare of individual
members of the household. Therefore, for any given household, an equivalence scale is used to
approximate the number of single adults, based on observed consumption behaviour. There are a
number of value judgments embedded in this practice; for example, differences in needs are reflected in
differences in consumption. Adult females and children are assigned a male equivalence of less than
one since they typically consume less; however, that may not mean that they have lower "needs" but
rather have less power within the household. The existence of size economies in consumption may also
mean that two people can live more cheaply together than apart (for a further discussion of these
issues, see Ravallion reference in section 7a below).
--Undernutrition: This is a distinct concept, although closely associated with poverty. Undernutrition can
be viewed as a specific type of poverty, namely food energy poverty. There are a number of arguments
for and against using this as a measure of well-being. A practical advantage is that this measure does
not have to be adjusted for inflation and would not be constrained by any inadequacy of price data.
Measures of child nutritional status can help capture aspects of welfare, such as distribution within the
household which are not adequately reflected in other indicators. However, nutrition is not the only
aspect that matters to the well-being of people, including the poor. Thus, poverty comparisons based
solely on nutrition alone may be limited and deceptive.
ii) Defining the Poverty Line: In practice, there are a number of alternative approaches to defining
poverty lines:
--Absolute poverty lines: An absolute poverty line is one which is fixed in terms of the living standard
indicator being used (consumption, nutrition). It is fixed over the entire domain of comparison, that is, a
poverty line which assures the same level of economic welfare would be used to measure and compare
poverty across provinces or different situations. The poverty line may still vary, but only so as to
measure the differences in the cost of a given level of welfare. Absolute poverty lines are more common
in developing country literature.
The most common approach to defining absolute poverty lines is to estimate the cost in each region or
at each date of a certain bundle of goods necessary to attain basic consumption needs (this is called the
basic needs approach). The most important component of basic needs is a recommended food energy
intake, supplemented by essential non-food goods. To measure food energy requirements, one needs
to make an assumption about activity levels which in turn determine energy requirements to maintain
the body's metabolic rate at rest. Once the food energy intake has been determined, and its cost has
been calculated, an allowance for non-food spending can be added by finding the total expenditure level
at which a person typically attains the food component of the poverty line. An alternative (lower)
allowance for non-food goods is to use the average non-food spending of people who can just afford the
food component of the poverty line: it can be argued that this is a reasonable lower bound for the nonfood component of the poverty line (see Ravallion reference in section 7a below).
--Relative poverty lines: These have dominated developed country literature where many studies have
used a poverty line which is set at, for example, 50% of the national mean income. When the poverty
line is fixed as a proportion of the national mean, if all incomes increase by the same proportion, there
would be no change in relative inequalities and the poverty line would simply increase by the same
proportion; that is, the poverty measure will not change. This can make such poverty lines deceptive for
some purposes, such as assessing whether poor people are better or worse off.
A cross-country comparison of 36 countries, both developed and developing, revealed that real poverty
lines will tend to increase with economic growth, but they will do so slowly for the poorest countries.
Therefore, the concept of absolute poverty appears to be more relevant to low income countries, while
relative poverty is of more relevance to high income countries.
(c) The Indicator in the DSR Framework: In the DSR Framework, this indicator represents a measure
of the State of poverty.
(d) Limitations of the Indicator: In practice, most applications in developing countries have used
consumption per person. This probably overstates the extent to which poverty is associated with larger
family sizes. But other aspects of the poverty profile (such as assessments of the regional or sectoral
poverty profiles) tend to be more robust as a measurement choice.
It is important to note that a certain amount of arbitrariness and value judgement are unavoidable in
defining individual welfare and any poverty line. Therefore, the overall assessment of the poverty
situation should pay particularly attention to how the choices made affect poverty comparisons, since
these are generally what matter most to policy implications. An increasingly common practice is to
recalculate the poverty measures using various poverty lines, and to test whether the qualitative poverty
comparisons are robust to the choice.
It should be noted that there are several comparability problems across countries in the use of data from
household surveys (see section 5 below). In addition, definitions of poverty are lacking in some
countries or vary from country to country. These problems are diminishing over time as survey
methodologies are improving and becoming more standardized, but they remain.
(e) Alternative Definitions: The Head Count Index and the Squared Poverty Gap Index represent
alternative definitions for a poverty indicator (see section 3c above and the relevant methodology sheets
for these indicators).
5. Assessment of the Availability of Data from International and National Sources
The most important source of data on living standards is household surveys. The results of these
surveys can be obtained from government statistical agencies, often via published reports. About two
thirds of the developing countries have done sample household surveys which are representative
nationally, and some (but certainly not all) of these provide high-quality data on living standards.
Data can also be obtained from international agencies such as The World Bank (mostly data for low and
middle income countries emerging from the Living Standards Measurement Study and Social
Dimensions of Adjustment Project for Sub Saharan Africa). Data for developed countries can be
obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or
the Organisation for Economic Co-operation and Development (OECD).
6. Agencies Involved in the Development of the Indicator
The lead agency involved is The World Bank (WB). The contact point is the Chief, Indicators and
Environmental Valuation Unit, Environment Department, WB; fax no. (1-202) 477 0968.
7. Further Information
(a) Further Readings:
Ravallion, M. Poverty Comparisons. Fundamentals in Pure and Applied Economics, Volume 56,
Harwood Academic Press, Switzerland. 1994.
SQUARED POVERTY GAP INDEX
Social
Chapter 3
State
1. Indicator
(a) Name: Squared Poverty Gap Index.
(b) Brief Definition: The mean of the squared proportionate poverty gap.
(c) Unit of Measurement: Fraction bounded by 0 and the Poverty Gap Index.
2. Placement in the Framework
(a) Agenda 21: Chapter 3: Combating Poverty.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: The most important purpose of a poverty measure is to enable poverty comparisons.
These are required for an overall assessment of a country's progress in poverty alleviation and/or the
evaluation of specific policies or projects. An important case of a poverty comparison is the poverty
profile which shows how the aggregate poverty measure can be decomposed into poverty measures for
various sub-groups of the population, such as by region of residence, employment sector, education
level, or ethnic group. A good poverty profile can help reveal a number of aspects of poverty-reduction
policies, such as the regional or sectoral priorities for public spending. Poverty comparisons are also
made over time, in assessing overall performance from the point of view of the poor.
(b) Relevance to Sustainable/Unsustainable Development: Measures of poverty are a very
significant consideration of sustainable development. The eradication of poverty remains a major
challenge for policy decision makers. Furthermore, an integrative viewpoint which simultaneously takes
account of development issues, resource use and environmental quality, and human welfare must be
taken if sustainable progress is to be achieved.
In addition to the Head Count and Poverty Gap Indices, a third measure which better reflects changes in
the severity of poverty is the Squared Poverty Gap Index. This is defined similar to the Poverty Gap
Index except that the poverty gaps are squared, thus giving the highest weighting to the largest poverty
gap. The need for this Index arises because the Poverty Gap Index may not adequately capture
concerns over distribution changes within the poor. For example, if a policy resulted in money transfer
from someone just below the poverty line to the poorest person, the Squared Poverty Gap Index will
reflect this change, while the Poverty Gap Index will not.
(c) Linkages to Other Indicators: In general, this indicator is linked to many other sustainable
development measures, for example, net migration rate, adult literacy rate, Gross Domestic Product per
capita, and population living below the poverty line in dryland areas. More specifically, the poverty
measures discussed in this and two other methodology sheets; namely the Head Count Index, the
Poverty Gap Index, and the Squared Poverty Gap Index; capture successively more detailed aspects of
the poverty situation. The Head Count Index measures how widespread poverty is, the Poverty Gap
Index measures how poor the poor are, and the Squared Poverty Gap Index measures the severity of
poverty by giving more weight to the poorest of the poor.
(d) Targets: Not available.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: A poverty measure is a summary statistic on the economic
welfare of the poor in a society. There is no one universally accepted single measure of poverty. A
number of different approaches exist (see, for example, the methodology sheets for the Poverty Gap
Index and the Squared Poverty Gap Index). This methodology sheet guides the reader along certain key
issues, such as the different approaches to measuring individual welfare, without prescribing decisions.
Consequently, it is directed at comparability over time within a given country, as it helps national
practitioners specify poverty indicators that match their specific situation and preferred approach.
However, this is at the expense of international comparability.
To compute poverty measures, the following questions related to identifying and defining the poor must
be addressed first:
i) How do we measure an individual's economic welfare?
ii) At what level of measured welfare is a person considered poor?
(b) Measurement Methods: The Squared Poverty Gap Index is the mean of a measure (weighted by
household-size) that is zero if the household's welfare (y) is above the poverty line (z), and represented
by the squared poverty gap, that is [1-y/z] x [1-y/z], if y is at or below z.
For computing the above indicator, estimates of individual economic welfare (y), and the poverty line (z)
are required.
i) Measuring Individual Welfare: There are a number of different approaches to measuring welfare. The
approaches differ in terms of the importance attached to the individual's own judgment of well-being
versus a concept of welfare decided upon by somebody else. The former would focus on measuring an
individual's consumption of a bundle of goods and services. An example of the latter would be defining
welfare by the level of nutritional intake, even though people do not live on food alone, or make food
choices solely on the basis of nutrition. Approaches in practice also differ according to how difficult it is
to obtain certain sorts of data in specific settings.
Typically one finds that poverty comparisons in developing countries put a high weight on nutritional
attainments, consistent with the behaviour of poor people in a specific society. A comprehensive
measure of consumption (for example, total expenditure on all goods and services consumed, including
non-market goods, such as consumption from a farmer's own product) has been more popular than
using current income in the development literature. This is due in part to the fact that incomes are harder
to measure accurately. Current consumption is also likely to give a better indication than current income
of a household's typical, long-term, economic welfare; income may fluctuate greatly over time,
particularly in rural economies (see Ravallion reference in section 7a below).
The following methods can be used for measuring individual standards of living:
--Consumption per equivalent male adult: Since households differ in size and composition, a simple
comparison of aggregate household consumption can be misleading about the welfare of individual
members of the household. Therefore, for any given household, an equivalence scale is used to
approximate the number of single adults, based on observed consumption behaviour. There are a
number of value judgments embedded in this practice; for example, differences in needs are reflected in
differences in consumption. Adult females and children are assigned a male equivalence of less than
one since they typically consume less; however, that may not mean that they have lower "needs" but
rather have less power within the household. The existence of size economies in consumption may also
mean that two people can live more cheaply together than apart (for a further discussion of these
issues, see Ravallion reference in section 7a below).
--Undernutrition: This is a distinct concept, although closely associated with poverty. Undernutrition can
be viewed as a specific type of poverty, namely food energy poverty. There are a number of arguments
for and against using this as a measure of well-being. A practical advantage is that this measure does
not have to be adjusted for inflation and would not be constrained by any inadequacy of price data.
Measures of child nutritional status can help capture aspects of welfare, such as distribution within the
household which are not adequately reflected in other indicators. However, nutrition is not the only
aspect that matters to the well-being of people, including the poor. Thus, poverty comparisons based
solely on nutrition alone may be limited and deceptive.
ii) Defining the Poverty Line: In practice, there are a number of alternative approaches to defining
poverty lines:
--Absolute poverty lines: An absolute poverty line is one which is fixed in terms of the living standard
indicator being used (consumption, nutrition). It is fixed over the entire domain of comparison, that is, a
poverty line which assures the same level of economic welfare would be used to measure and compare
poverty across provinces or different situations. The poverty line may still vary, but only so as to
measure the differences in the cost of a given level of welfare. Absolute poverty lines are more common
in developing country literature.
The most common approach to defining absolute poverty lines is to estimate the cost in each region or
at each date of a certain bundle of goods necessary to attain basic consumption needs (this is called the
basic needs approach). The most important component of basic needs is a recommended food energy
intake, supplemented by essential non-food goods. To measure food energy requirements, one needs
to make an assumption about activity levels which in turn determine energy requirements to maintain
the body's metabolic rate at rest. Once the food energy intake has been determined, and its cost has
been calculated, an allowance for non-food spending can be added by finding the total expenditure level
at which a person typically attains the food component of the poverty line. An alternative (lower)
allowance for non-food goods is to use the average non-food spending of people who can just afford the
food component of the poverty line: it can be argued that this is a reasonable lower bound for the nonfood component of the poverty line (see Ravallion reference in section 7a below).
--Relative poverty lines: These have dominated developed country literature where many studies have
used a poverty line which is set at, for example, 50% of the national mean income. When the poverty
line is fixed as a proportion of the national mean, if all incomes increase by the same proportion, there
would be no change in relative inequalities and the poverty line would simply increase by the same
proportion; that is, the poverty measure will not change. This can make such poverty lines deceptive for
some purposes, such as assessing whether poor people are better or worse off.
A cross-country comparison of 36 countries, both developed and developing, revealed that real poverty
lines will tend to increase with economic growth, but they will do so slowly for the poorest countries.
Therefore, the concept of absolute poverty appears to be more relevant to low income countries, while
relative poverty is of more relevance to high income countries.
(c) The Indicator in the DSR Framework: In the DSR Framework, this indicator represents a measure
of the State of poverty.
(d) Limitations of the Indicator: In practice, most applications in developing countries have used
consumption per person. This probably overstates the extent to which poverty is associated with larger
family sizes. But other aspects of the poverty profile (such as assessments of the regional or sectoral
poverty profiles) tend to be more robust as a measurement choice.
It is important to note that a certain amount of arbitrariness and value judgement are unavoidable in
defining individual welfare and any poverty line. Therefore, the overall assessment of the poverty
situation should pay particularly attention to how the choices made affect poverty comparisons, since
these are generally what matter most to policy implications. An increasingly common practice is to
recalculate the poverty measures using various poverty lines, and to test whether the qualitative poverty
comparisons are robust to the choice.
It should be noted that there are several comparability problems across countries in the use of data from
household surveys (see section 5 below). In addition, definitions of poverty are lacking in some
countries or vary from country to country. These problems are diminishing over time as survey
methodologies are improving and becoming more standardized, but they remain.
(e) Alternative Definitions: The Head Count Index and the Poverty Gap Index represent alternative
definitions for a poverty indicator (see section 3c above and the relevant methodology sheets for these
indicators).
5. Assessment of the Availability of Data from International and National Sources
The most important source of data on living standards is household surveys. The results of these
surveys can be obtained from government statistical agencies, often via published reports. About two
thirds of the developing countries have done sample household surveys which are representative
nationally, and some (but certainly not all) of these provide high-quality data on living standards.
Data can also be obtained from international agencies such as The World Bank (mostly data for low and
middle income countries emerging from the Living Standards Measurement Study and Social
Dimensions of Adjustment Project for Sub Saharan Africa). Data for developed countries can be
obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or
the Organisation for Economic Co-operation and Development (OECD).
6. Agencies Involved in the Development of the Indicator
The lead agency involved is The World Bank (WB). The contact point is the Chief, Indicators and
Environmental Valuation Unit, Environment Department, WB; fax no. (1-202) 477 0968.
7. Further Information
(a) Further Readings:
Ravallion, M. Poverty Comparisons. Fundamentals in Pure and Applied Economics, Volume 56,
Harwood Academic Press, Switzerland. 1994.
GINI INDEX OF INCOME INEQUALITY
Social
Chapter 3
State
1. Indicator
(a) Name: Gini Index of Income Inequality.
(b) Brief Definition: A summary measure of the extent to which the actual distribution of income,
consumption expenditure, or a related variable, differs from a hypothetical distribution in which each
person receives an identical share.
(c) Unit of Measurement: A dimensionless index scaled to vary from a minimum of zero to a maximum
of one; zero representing no inequality and one representing the maximum possible degree of
inequality.
2. Placement in the Framework
(a) Agenda 21: Chapter 3: Combating Poverty.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: The Gini Index provides a measure of income or resource inequality within a population. It
is the most popular measure of income inequality.
(b) Relevance to Sustainable/Unsustainable Development: This indicator is particularly relevant to
the equity component of sustainable development. Income or resource distribution have direct
consequences on the poverty rate of a country or region. Broadly speaking, average material welfare
can be defined by the per capita Gross Domestic Product (GDP). However, statistical averages can
mask the diversity that exists within any country. Therefore, from a sustainable development
perspective, it is informative to examine income and wealth distribution throughout a population. A
country can, for example, have a high per capita GDP figure, but its income distribution so skewed that
the majority of people are poor. This indicator is useful both to measure changes in income inequality
over time and for international comparisons.
(c) Linkages to Other Indicators: This indicator is linked to several other sustainable development
measures, including the poverty indicators, women per 100 men in the labour force, GDP per capita,
population dynamics in mountain areas, and sustainable development strategies.
(d) Targets: Not available.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The concept and definition of this indicator are well
understood and readily available. The Gini Index measures the area between the Lorenz Curve and a
hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line of
perfect equality (see Figure 1 in section 4b below). The Gini Index is defined as one half of the average
value of the absolute differences between all possible pairs of "incomes".
(b) Measurement Methods: The Lorenz Curve plots the cumulative percentages of total income
received (on the vertical axis) against the cumulative percentage of recipients, starting with the poorest
individual or household (see Figure 1).
Figure 1: The Lorenz Curve and Gini Index of Income
There are a number of choices about data which can influence the precise value of the Gini Index
obtained. For example, a Gini Index for consumption expenditure will typically be lower in value than
one for income, even within the same population. This is because households smooth their consumption
over time in response to income changes. At any one date, there will be some households with
unusually low incomes and others with unusually high ones; with some opportunities for saving and/or
borrowing. Thus, household consumption will be less unequal.
It is important how "income" is measured, for example whether it is total household income or per capita
household income, or income per equivalent adult. In addition, it matters whether or not the incomes are
weighted by household size, since households with lower income per person tend to be larger. Thus, the
income share of the poorest 20% of households will be higher than the income share of the poorest 20%
of persons.
The World Bank, for example, prefers to weight by household size and calculate the shares held by
persons rather than households for most purposes. As a general rule, the Bank also considers
consumption expenditure to be the more reliable indicator of welfare than income, which can be
excessively variable over time, and is also more difficult to measure accurately, particularly in
developing countries. Looking at the sample of 67 low and middle income countries for which Gini
indices of income are reported in the World Bank's draft report World Development Indicators, this
coefficient ranges from a low of 22% to a high value of 64%.
There are a number of ways of estimating the Gini Index of income, and the choice depends in part on
the type of data available. Distributional data are often available in grouped form, such as the income
share of the lowest decile of households, where households are ranked by income per person. To
estimate the Lorenz Curve, and thus the Gini Index, from such data, the World Bank often uses a
software package called POVCAL. Having specified the type of data, the program calculates both the
General Quadratic specification for the Lorenz Curve and the Beta specification. It then calculates the
Gini Index and various other statistics, including poverty measures for each Lorenz Curve. The program
also advises which is the better specification for the Lorenz Curve for the specific data used.
(c) The Indicator in the DSR Framework: In the DSR Framework, this indicator represents a measure
of the State of income inequality.
(d) Limitations of the Indicator: The Gini Index is not a very discriminating indicator. Two very different
distributions--one having more inequality amongst the poor, the other having more amongst the rich-can have exactly the same Gini Index.
Measurement errors in data sets are thought to be greater for incomes compared to consumption
expenditure, which will add to measured inequality (see section 4b above). Differences between
countries in the measured Gini index may thus reflect in part differences in the welfare measures used.
While the Gini Index of income (in common with most other measures of inequality) captures information
on the pattern of relative levels of wellbeing in the population, it is independent of any considerations of
absolute living standards. So there is nothing to guarantee that a lower Gini Index of income entails
higher social welfare in any agreed sense, since the mean income may have also fallen. The Gini Index
is at best a partial indicator, and other measures will be needed to complete the picture of how levels of
economic welfare are evolving in a society.
It should be noted that there are several comparability problems across countries in the use of data from
household surveys (see section 5 below). These problems are diminishing over time as survey
methodologies are improving and becoming more standardized, but they remain.
(e) Alternative Definitions: There are many other measures of inequality, with various strengths and
weaknesses. These are discussed in Sen (1973) (see section 7a below).
5. Assessment of the Availability of Data from International and National Sources
The most important source of data on living standards is household surveys. The results of these
surveys can be obtained from government statistical agencies, often via published reports. About two
thirds of the developing countries have done sample household surveys which are representative
nationally, and some (but certainly not all) of these provide high-quality data on living standards.
Data can also be obtained from international agencies such as The World Bank (mostly data for low and
middle income countries emerging from the Living Standards Measurement Study and Social
Dimensions of Adjustment Project for Sub Saharan Africa). Data for developed countries can be
obtained from the Statistical Office of the European Union (Eurostat), the Luxembourg Income Study, or
the Organisation for Economic Co-operation and Development (OECD).
6. Agencies Involved in the Development of the Indicator
The lead agency involved is The World Bank (WB). The contact point is the Chief, Indicators and
Environmental Valuation Unit, Environment Department, WB; fax no. (1-202) 477 0968.
7. Further Information
(a) Further Readings:
Chen, S., G. Datt, M. Ravallion. POVCAL: A Program for Calculating Poverty Measures from Grouped
Data. Poverty and Human Resources Division, Policy Research Department, Washington DC: World
Bank. 1992.
Ravallion, M., and S. Chen. What Can New Survey Data Tell Us About Recent Changes in Living
Standards in Developing and Transitional Economies?. Working Paper 1. Research Project on Social
and Environmental Consequences of Growth-Oriented Policies, Washington DC: World Bank.
Sen, A. On Economic Inequality. Oxford: Oxford University Press. 1973.
The World Bank. World Development Indicators. Draft Report. 1996.
RATIO OF AVERAGE FEMALE WAGE TO MALE WAGE
Social
Chapter 3
State
1. Indicator
(a) Name: Ratio of average female wage to male wage.
(b) Brief Definition: Obtained as the quotient of average wage rates paid to female and male
employees at regular intervals for time worked or work done for particular occupations.
(c) Unit of Measurement: %.
2. Placement in Framework
(a) Agenda 21: Chapter 3: Combating Poverty
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: It is important to have an assessment of remuneration offered women vis-a-vis their male
counterpart to ultimately determine the level of women's participation in the economy.
(b) Relevance to Sustainable/Unsustainable Development: The lower the ratio of wages offered to
women, the less the attraction for women to join the labor force, which in turn deprives the economy of a
vital component of development. This disadvantage could also be attributed to inequalities in
educational opportunities for women and the need for policy makers to correct this inequity. It is
generally acknowledged that if women are more educated, it is likely to result in a corresponding
reduction in infant mortality rates.
(c) Linkages to Other Indicators: The indicator has close linkages with the unemployment rate
indicator because both deal with employment as a principal generator of production. It is also closely
linked to indicators pertaining to education.
(d) Targets: Not available.
(e) International Conventions and Agreements: The resolution covering the institution of an
integrated system of wages statistics, including defined earnings and wage rates, was adopted by the
Twelfth International Conference of Labor Statisticians in Geneva in 1973 (see section 7 below).
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The UN International Labour Office (ILO) and the UN
System of National Accounts (SNA) provide two sources for this section.
i) The concept of earnings, as applied in wages statistics, relate to remuneration in cash and in kind paid
to employees, usually at regular intervals, for time worked; or work done together with remuneration for
time not worked, such as for annual vacation, other paid leave or holidays. Wage rates, as part of
earnings, include basic wages, cost-of-living allowances and other guaranteed and regularly paid
allowances, but exclude overtime payments, bonuses and gratuities, family allowances and other social
security payments made by employers. Ex gratia payments in kind, supplementary to normal wage rates
are also excluded (ILO).
ii) Wages and salaries, as part of compensation to employees, are payable in cash or in kind and
include the values of any social contributions, such as income taxes, payable by the employee even if
they are actually withheld by the employer for administrative convenience or other reasons and paid
directly to social insurance schemes, tax authorities, etc. on behalf of the employee. Wages and salaries
in cash include payments at regular intervals, supplementary allowances payable regularly, payments to
employees away from work for short periods such as holidays, and ad hoc bonuses linked to
performance, commissions, gratuities and tips (SNA).
(b) Measurement Methods: The indicator is measured by taking the average wage rates per day, week
or month received by female employees as a ratio of the corresponding average wage rates for males. It
could be classified further according to major divisions of economic activity, for example, agriculture,
mining and quarrying, etc., to facilitate measurement of sectoral impact on the development process.
Similarly, breakdowns according to age classes would provide additional information related to
sustainable development trends.
(c) The Indicator in the DSR Framework: This indicator deals with the participation of labor in the
economic process, and stresses the importance of human activities to sustainable development. It fits
ideally within the DSR Framework as a State indicator.
(d) Limitations of the Indicator: A serious limitation is the reliability and comprehensiveness of wage
rate data paid to female labor. Although data is available for many countries, the quality varies
significantly among countries. Wage rates determine total remuneration and measure women's
contribution to total production. However, since most of the basic remuneration for women's economic
and social activities remain unreported or unrecorded--and even if reported, are grossly undervalued-only imputations are possible in many countries. The indicator will be greatly influenced by the selection
of wage sectors, and type and level of job. The cost of collecting the data from questionnaires and
surveys can be significant.
Another limitation is that female wage rates do not tell the whole story. Wages, particularly for females,
may reflect under-employment. Women, especially in developing countries, may participate in informal
activities where they are not classified as wage earners. They do not receive income in the SNA sense
and therefore these activities are not covered by this indicator.
(e) Alternative Indicator Definitions: An alternative indicator to the male-female wage would be the
percentage contribution of women to GDP which measures activities in the production boundary that
incorporate the contribution of women in the economic process as proposed in the 1993 SNA. This
would include the production and processing of agricultural, dairy and fishery products and flour by
milling; weaving, dress making, production of footwear, baskets, mats, etc.
5. Assessment of the Availability of Data from National and International Sources
The average wage rates paid to female and male employees provide the basic information to compile
this indicator and are mainly reported by departments or ministries of labor in most countries. It is
obtained either through questionnaires or surveys from the different economic sectors of the economy.
Average earnings are usually derived from payroll data supplied by a sample of establishments together
with data on hours of work and on employment. Occasionally, wage indices are reported in the absence
of absolute wage data. In some other cases, information is compiled on the basis of social insurance
statistics. The extent of data availability is published by the ILO in the Yearbook of Labor Statistics.
6. Agencies Involved in the Development of the Indicator
The International Labor Office (ILO) is the principal agency and contact point in the development of this
indicator. The contact is the Focal Point for Environment and Sustainable Development; fax no. (41 22)
798 8685.
7. Further Information
The full text of the resolution listed in section 3e above can be found in Current International
Recommendations on Labor Statistics (Geneva 1988).
Further information can be obtained from other ILO publications, as follows:
An Integrated System of Wages Statistics: A Manual on Methods (Geneva 1979).
Statistical Sources and Methods; Vol. 2 Employment, Wages and Hours of Work (Establishment
Surveys) (Geneva 1987); Vol. 4 Employment, Unemployment, Wages and Hours of Work
(Administrative Records and Related Sources) (Geneva 1989).
Chapter 5: Demographic dynamics and sustainability

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Population growth rate
Net migration rate
Total fertility rate
Population density
Chapter 5: Demographic dynamics and sustainability
POPULATION GROWTH RATE
Social
Chapter 5
Driving Force
1. Indicator
(a) Name: Population growth rate.
(b) Brief Definition: The average annual rate of change of population size during a specified period.
(c) Unit of Measurement: Usually expressed as a percentage.
2. Placement in the Framework
(a) Agenda 21: Chapter 5: Demographic Dynamics and Sustainability.
(b) Type of Indicator: Driving Force.
3. Significance (Policy Relevance)
(a) Purpose: The population growth rate measures how fast the size of the population is changing.
(b) Relevance to Sustainable/Unsustainable Development: Agenda 21 identifies population growth
as one of the crucial elements affecting long-term sustainability (see especially paragraphs 5.3 and
5.16). Population growth, at both national and subnational levels, represents a fundamental indicator for
national decision makers. Its significance must be analyzed in relation to other factors affecting
sustainability. However, rapid population growth can place strain on a country's capacity for handling a
wide range of issues of economic, social, and environmental significance, particularly when rapid
population growth occurs in conjunction with poverty and lack of access to resources, or unsustainable
patterns of production and consumption, or in ecologically vulnerable zones (see paragraphs 3.14, 3.25
and 3.26 of the ICPD Programme of Action).
(c) Linkages to Other Indicators: There are close linkages between this indicator and other
demographic and social indicators, as well as all indicators expressed in per capita terms (for example,
GDP per capita). Population growth usually has implications for indicators related to education,
infrastructure, and employment. It is also related to human settlements and the use of natural resources,
including sink capacities. Population growth can increase environmental degradation, although this is
not always the case.
(d) Targets: International agreements do not establish national or global targets. A number of national
governments have adopted numerical targets for the rate of population growth. In 1993, 11 percent of
governments considered their rates of population growth to be too low, 45 percent were satisfied with
the rate, and 44 percent considered it to be too high.
(e) International Conventions and Agreements: Not available (See 3d above).
4. Methodological Description and Underlying Definitions
The underlying concept of population growth rate as an indicator is well-known. For a country, it is
generally based on either (i) an intercensal population growth rate calculated from two censuses, each
adjusted for incompleteness; or (ii) from the components of population growth (adjusted for
incompleteness, when necessary) during a period, namely, numbers of births, deaths and migrants.
5. Assessment of the Availability of Data from International and National Sources
As indicated above, the population growth rate can be calculated either from census data or from
registration data (births, deaths and migrants). The United Nations recommends that countries take
censuses every 10 years, and these data can be used to calculate an intercensal population growth
rate. In recent decades most countries have carried out censuses and is widely available. For example,
204 countries or areas carried out a census during the 1990 census decade (1985 to 1994). Data on
births, deaths and migrants may come from national registration systems or from special questions in
demographic surveys and censuses.
National and sub-national census data, as well as data on births, deaths and migrants, are available for
the large majority of countries from national sources and publications; as well as from special country
questionnaires sent to national statistical offices from the Statistical Division, UN Department of
Economics and Social Information and Policy Analysis (DESIPA). For all countries, census and
registration data are evaluated and, if necessary, adjusted for incompleteness by the Population
Division, DESIPA as part of its preparations of the official United Nations population estimates and
projections. Past, current and projected population growth rates are prepared for all countries by the
Population Division, DESIPA and appear in the United Nations publication, World Population Prospects:
The 1994 Revision (see item 7, below).
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations DESIPA. The contact point is the Director, Population
Division, DESIPA; fax no. (1 212) 963 2147.
7. Further Information
Further references include:
Population Division, DESIPA, World Population Prospects: The 1994 Revision (United Nations
publication Sales No. E.95.XIII.16, New York, 1995).
Population Division, DESIPA, Manual X: Indirect Techniques for Demographic Estimation (United
Nations Sales No. E.83.XIII.2, New York, 1983).
Population Division, DESIPA, World Urbanization Prospects: The 1994 Revision (United Nations
publication Sales No. E.95.XIII.12, New York, 1995).
Population Division, DESIPA, MORTPAK-LITE - The United Nations Software Package for Mortality
Measurement (United Nations, New York, 1988).
Statistical Division/DESIPA, 1993 Demographic Yearbook, (United Nations Sales No. E/F.95.XIII.1,
1995).
For information about government policies regarding this indicator see:
United Nations, World Population Monitoring, 1993 (United Nations Sales No. E.95.XIII.8., New York,
1995).
United Nations, Results of the Seventh United Nations Population Inquiry Among Governments (New
York, 1995, ST/ESA/SER.R/140).
NET MIGRATION RATE
Social
Chapter 5
Driving Force
1. Indicator
(a) Name: Net migration rate.
(b) Brief Definition: Ratio of the difference between the number of in-migrants and out-migrants from a
particular area during a specified period to the average population of that area during the period
considered. International and internal migration are discussed separately in sections 4 and 5 below.
(c) Unit of Measurement: The indicator is usually expressed as per thousand population.
2. Placement in the Framework
(a) Agenda 21: Chapter 5: Demographic Dynamics and Sustainability
(b) Type of Indicator: Driving Force.
3. Significance (Policy Relevance)
(a) Purpose: The net migration rate measures geographical mobility of population. Migration is one of
the basic demographic events -- birth and death are the others -- that directly influence the size of
population in an area.
(b) Relevance to Sustainable/Unsustainable Development: Net migration is a major force of
demographic redistribution. At the international level, migration (people) is one of three important flows
along with commodities (goods and services), and capital (money), that go beyond the traditional
boundaries of a sovereign state. Within countries, migration both influences and is influenced by
economic, social, environmental and political events. Increases of net migration linked to a loss of
livelihood can be a symptom of unsustainability.
Migration is often seen as an economic phenomenon--in discussions of labour migration from rural to
urban areas or from the developing countries to the developed countries, for example. It can also be a
political phenomenon, as with asylum seekers and refugees. Recently, linkages with environmental
factors are receiving increasing attention, as in the cases of "environmental refugees" and migration to
ecologically fragile areas. The significance of migration to national policy makers does not rest only in its
size, but also in its composition. Such migrant characteristics as age, sex, fertility level, educational
background, occupation, and skill levels have profound implications for development in both the sending
and the receiving areas or countries.
(c) Linkages to Other Indicators: The net migration rate is considered to have strong associations with
economic, social, and environmental indicators. There are close linkages between this indicator and
other demographic indicators, including urbanization-related indicators. In addition, migration rates can
be associated with natural resource depletion, desertification, and land use change.
(d) Targets: International agreements do not establish national or global targets. Nearly all national
governments regulate international migration, and many governments have policies intended to
influence internal migration flows.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: See section 4b below.
(b) Measurement Methods:
i) Net internal migration rate: The net migration rate for particular areas within a country is usually
estimated on the basis of the number of persons reporting that they changed residence from outside to
within the area of interest during a given period and those reporting that they changed residence from
within to without the area of interest during the same period. Those reports are usually made only at the
time of a census. A few countries maintaining continuous population registers have access to the
required information on a yearly basis. Both censuses and population registers also produce information
on the total population in the area of interest that allows the estimation of the denominator for the
calculation of a net migration rate. When reliable direct information about in- and out-migration is
unavailable, net migration can be estimated indirectly, as a residual factor when other sources of
population change--births, deaths, and, in some cases, changes of boundaries of cities or other units-have been estimated separately (see section 5b below).
ii) Net international migration rate: Ideally, the net migration rate for a country should be derived directly
from the number of immigrants to and emigrants from that country over a given period, and a count of
the average population size of the country during that period. However, few countries gather sufficiently
comprehensive international migration statistics on a continuous basis to allow direct calculation of the
net migration rate. Therefore, the rate must often be estimated indirectly from other information. The
most common estimation approach is to calculate the net migration rate as the difference between the
growth rate of a country's population over a certain period and the rate of natural increase of that
population (itself being the difference of the birth rate and the death rate). Such calculations are usually
made for intercensal periods. Before estimating the net migration rate in this way, data must be
evaluated and, if necessary, adjusted for differential levels of census under-enumeration between
censuses and for errors in the estimation of the birth or death rates of a country. Other indicators of
migration such as the percentage of the population born outside the country (a "stock" measure) are
often used instead of the net migration rate.
(c) The Indicator in the DSR Framework: The indicator is a subcomponent of population change. As
such it is regarded as a Driving Force indicator.
(d) Limitations of the Indicator: The definitions of immigrant and emigrant used by different countries
and even for different data sources within a single country vary considerably, thus compromising the
comparability and interpretation of the indicator. The data are often poorly measured restricting the
usefulness for modelling purposes. Illegal immigrants are not captured by the census or survey
statistics.
(e) Alternative Definitions: Alternative indicators of international migration, such as the stock of
foreign-born persons in a country, are often used.
5. Assessment of the Availability of Data from National and International Sources
i) Net internal migration rate: Censuses are the major source of information on internal migration. They
vary, however, in the type of data they collect and the way in which the information obtained is coded
and tabulated. The questions most commonly included in censuses that indicate the occurrence of some
change of residence are: current place residence and place of residence at a specific time before the
census; current and previous place of residence, and length of stay in current residence; place of birth.
Most countries code place of residence in terms of major geographical subdivision (state, department,
province etc.) although use of a finer subdivision of the territory is often useful. Some countries record
the urban or rural nature of the place of residence involved. However, net rural-urban migration is more
likely to be derived from indirect estimation procedures than directly from census data. In general, data
on internal migration gathered by censuses remain underexploited and there is no comprehensive
source of information of net migration rates between different units within countries, except for countries
with a population register.
(ii) Net international migration rate: Direct and comprehensive data on international migration
movements are not available for most countries or areas of the world. However, the Population Division,
UN Department of Economics and Social Information and Policy Analysis (DESIPA) takes into account
the available direct and indirect evidence to derive net migration estimates, which are published as part
of the biennial estimates and projections of population. Population registers are the data sources most
likely to yield the information needed to calculate the net migration rate, but only a few developed
countries maintain such registers. Immigration statistics derived from the administrative procedures
involved in admitting foreigners for residence do not provide good measures of flows nor are they
sufficiently comprehensive to permit the estimation of migration rates as they do not reflect the migration
of citizens. In a few countries, arrival and departure statistics derived as part of migration control at ports
of entry provide information on the number of immigrants and emigrants. However, most countries
gathering arrival and departure statistics fail to differentiate international migrants from other travellers
and consequently those data cannot be used to derive net migration rates.
For both internal and international migration, both absolute data and rate of change are required by
policy makers. The composition of migrants would also be useful.
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations DESIPA. The contact point is the Director, Population
Division, DESIPA; fax no. 1 212 963 2147.
7. Further information
i) Net internal migration rate
Patterns of Urban and Rural Population Growth (United Nations publication, Sales No. E.79.XIII.9).
Internal Migration of Women in Developing Countries (United Nations publication, Sales No. E.94.XIII.3).
Courgeau, Daniel, Méthodes de Mesure de la Mobilité Spatiale (Institut National d'Etudes
Démographiques, Paris, 1988).
ii) Net international migration rate
World Population Prospects: The 1994 Revision (United Nations publication, Sales No. E.95.XIII.16,
New York, 1995).
1989 Demographic Yearbook (United Nations publication, Sales No. E/F.90.XIII.1).
Trends in Total Migrant Stock, Revision 1, database maintained by the Population Division, DESIPA,
1995 (POP/1B/DB/95/1).
Recommendations on International Migration Statistics (United Nations publication, Sales No.
F.79.XVII.18).
Consolidated Statistics of all International Arrivals and Departures: A Technical Report (United Nations
publication, Sales No. E.85.XVII.8).
National Data Sources and Programmes for Implementing the United Nations Recommendations on
Statistics of International Migration (United Nations publication, Sales No. E.86.XVII.22).
Measuring International Migration: Theory and Practice, International Migration Review (Staten Island,
New York), vol. 21, No. 4 (Winter).
TOTAL FERTILITY RATE
Social
Chapter 5
Driving Force
1. Indicator
(a) Name: Total fertility rate.
(b) Brief Definition: The average number of children that would be born to a woman in her lifetime, if
she were to pass through her childbearing years experiencing the age specific fertility rates for a given
period.
(c) Unit of Measurement: The total fertility rate is usually expressed as per woman or per thousand
women.
2. Placement in the Framework
(a) Chapter 5: Demographic Dynamics and Sustainability.
(b) Type of Indicator: Driving Force.
3. Significance
(a) Purpose: This is one of the most commonly used summary indicators of the level of fertility. An
important property of the total fertility rate is that it is not affected by the age distribution of the
population, although it can be affected by rapid changes in birth timing.
(b) Relevance to Sustainable/Unsustainable Development: The International Conference on
Population and Development (ICPD) Programme of Action encourages countries to take the necessary
steps to complete a demographic transition, understanding that an imbalance between demographic
rates and social, economic and environmental goals, together with unsustainable patterns of production
and consumption, has serious implications for sustainable development. In countries where fertility is
still high, large young populations create major challenges for health services, education and
employment (paragraphs 6.3, 6.4, and 6.6). As such it represents a leading indicator of future change.
(c) Linkages to Other Indicators: This indicator has close linkages with other demographic indicators,
particularly with the population growth rate. The ICPD Programme of Action also emphasizes the
interrelationships between fertility and mortality levels, the empowerment of women, and education
particularly of women and girls.
(d) Targets: International agreements do not establish specific national or global targets, although the
ICPD Programme of Action encourages Governments to bring about the demographic transition. Some
national governments have established quantitative goals for total fertility rate. As of 1993, 12 per cent
of governments perceived their levels of fertility as being too low, 44 per cent as satisfactory, and 45 per
cent as too high (sec DESIPA, World Population Monitoring, 1995 listed in section 7 below).
(e) International Conventions and Agreements: See section 3d above.
4. Methodological Description and Underlying Definitions
Where data on births by age of mother are of good quality, or adjustments for age miss-statement and
incompleteness can be made, the total fertility rate is directly calculated as the sum of age-specific
fertility rates, or five times the sum if data are given in five-year age groups. (An age-specific fertility rate
is calculated as the ratio of annual births to women at a given age to the population of women of the
same age.) When data on births by age of mother are unavailable from registration systems or maternity
history data in sample surveys, the total fertility rate can be calculated through indirect methods based
on special questions asked in censuses or demographic surveys. For information on these indirect
estimates, see Manual X and U.C. - LITE (see section 7 below).
5. Assessment of the Availability of Data from National and International Sources
Collected by the United Nations on a regular basis and available for most countries from vital
registration systems or surveys. For all countries, census and registration data are evaluated and, if
necessary, adjusted for incompleteness by the Population Division, Department of Economics and
Social Information and Policy Analysis (DESIPA) as part of its preparations of the official United Nations
population estimates and projections. Past, current and projected population growth rates are prepared
for all countries by the Population Division, DESIPA and appear in the United Nations publication, World
Population Prospects: The 1994 Revision (see section 7 below).
Most countries tabulate data from birth registration systems at the sub-national level. Surveys are
generally designed to provide estimates for major regions within countries as well as at the national
level. Less frequently the sample design permits the examining action of this indicator at state, provincial
or lower administrative levels.
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations Department of Economics and Social Information a Policy
Analysis (DESIPA). The contact point is the Director, Population Division, DESIPA; fax no. (1 212) 9632147.
7. Further Information
Population Division, DESIPA, World Population Prospects: The 1994 Revision (United Nations Sales
No. E.95.XIII.16, New York, 1995).
Population Division, DESIPA, Manual X: Indirect Techniques for Demographic Estimation (United
Nations Sales No. E.83.XIII.2, New York, 1983).
Population Division, DESIPA, MORTPAK-LITE - The United Nations Software Package for Mortality
Measurement (United Nations, New York, 1988).
Population Division, DESIPA, World Population Monitoring, 1993 (United Nations publication, Sales No.
E. 95.XIII.8, New York, 1995).
Programme of Action of the International Conference on Population and Development, Report of the
International Conference on Population and Development, Cairo, Egypt, September 5-13, 1994. (United
Nations Document - A/CONF. 171/13).
Statistical
Division,
DESIPA,
No.E/F.95.XIII.1,1995).
1993
Demographic
Yearbook
(United
Nations
POPULATION DENSITY
Social
Chapter 5
State
1. Indicator
(a) Name: Population density.
(b) Brief Definition: The total population size of a country or area divided by its surface area.
(c) Unit of Measurement: Usually expressed as population per square kilometer.
Sales
2. Placement in the Framework
(a) Agenda 21: Chapter 5: Demographic Dynamics and Sustainability.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: This indicator measures concentration of the human population in reference to space.
Population density can be used as a partial indicator of human requirements and activities in an area.
More refined indicators--such as number of persons per unit of habitable or cultivable land--may be
more useful for analytic purposes. Similarly, disaggregation of the indicator to urban size categories
would be useful in conjunction with other human settlement indicators.
(b) Relevance to Sustainable/Unsustainable Development: This indicator is most useful at the subnational level. Agenda 21 makes specific references to population density in relation to desertification
(Chapter 12) and to freshwater and solid wastes in urban areas (Chapters 18 and 21). In rural areas,
demographic factors, working interactively with other factors such as ecological endowments and
commercialization of agriculture, may place pressure on land resources. Higher or growing population
density can threaten sustainability of protected forest area and ecologically fragile or marginal land. At
the same time, population density is considered by some to be a driving-force of technological change in
production, and high concentration of population in a limited area is the main defining feature of urban
areas. High concentration of population also means more local demand for employment, housing,
amenities, social security and services, and environmental infrastructure for sanitation and waste
management, which may tax governments' management ability.
(c) Linkages to Other Indicators: This indicator has close linkages with other demographic indicators,
particularly the population growth rate, net migration rate, life expectancy at birth and total fertility rate as
well as human settlement indicators. In order to understand impacts of this indicator, it should be
examined in conjunction with location of resources and systems of production and distribution. Higher
population densities generally mean increased reliance on resource imports and the export of goods, as
well as environmental impacts such as solid waste disposal, and emissions to air and water. Areas with
high population densities tend to rely on the resources of less populated hinterlands, and thereby
increase the risk of exceeding regional carrying capacities for stock and sink resources. With subnational data, relationships to ecosystems, urban issues, and arable land, for example, can be
addressed at a more local level.
(d) Targets: International agreements do not establish national or global targets.
(e) International Conventions and Agreements: Not available (see section 3d above).
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: This indicator is well established.
(b) Measurement Methods: By definition, population density is calculated as population size divided by
surface area. Surface area data, as collected by the Statistical Division, UN Department of Economics
and Social Information and Policy Analysis (DESIPA), represent the total surface area, comprising land
area and inland waters (assumed to consist of major rivers and lakes) and excluding only polar regions
and uninhabited islands. In practice, the definition differs among countries, but is sufficiently comparable
for interpretation and analysis.
(c) The Indicator in the DSR Framework: Population density represents a demographic State
indicator.
(d) Limitations of the Indicator: The significance of the indicator is limited in countries which serve as
international hinterlands importing all their food and natural resources. Large uninhabited areas, such as
deserts, tend to distort the indicator. Disaggregation to the ecumene, or other sub-national areas, may
be difficult in many countries.
(e) Alternative Definitions: Total land area instead of total area could represent a useful alternative
definition.
5. Assessment of the Availability of Data from International and National Sources
Collected by the United Nations on a regular basis and available for all countries at the national level.
For all countries, the population data, which provide the numerator for calculating density, are evaluated
and, if necessary, adjusted for incompleteness by the Population Division/DESIPA as part of its
preparations of the official United Nations population estimates and projections. Past, current and
projected population figures for population density are prepared for all countries by the Population
Division/DESIPA and appear in the United Nations publication, World Population Prospects: The 1994
Revision (see section 7 below).
Population density can be calculated for sub-national areas from census data available in most
countries. The United Nations does not produce sub-national estimates of population density. However,
such estimates are available from certain regional institutions, such as Eurostat.
6. Agencies Involved in the Development of the Indicator
The lead agency is the United Nations Department for Economic and Social Information and Policy
Analysis (DESIPA). The contact point is the Director, Population Division, DESIPA; fax no. (1 212) 963
2147).
7. Further Information
Population Division, DESIPA, World Population Prospects: The 1994 Revision (United Nations Sales
No. E.95.XIII.16, New York, 1995).
Statistical Division, DESIPA, 1993 Demographic Yearbook (United Nations Sales No.E/F.95.XIII.1,
1995).
Chapter 36: Promoting education, public awareness and training











Rate of change of school-age population
Primary school enrolment ratio--gross
Primary school enrolment ratio--net
Secondary school enrolment ratio--gross
Secondary school enrolment ratio--net
Adult literacy rate
Children reaching grade 5 of primary education
School life expectancy
Difference between male and female school enrolment ratios
Women per hundred men in the labour force
GDP spent on education
Chapter 36: Promoting education, public awareness and
training
RATE OF CHANGE OF SCHOOL-AGE POPULATION
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Rate
of
change
of
school-age
population.
(b) Brief Definition: The average annual rate of change of school-age population size during
a
specified
period.
(c) Unit of Measurement: Usually expressed as a percentage.
2. Placement in the Framework
(a) Agenda 21: Chapter 36: Promoting Education, Public Awareness and Training.
(b) Type of Indicator: Driving Force.
3. Significance (Policy Relevance)
(a) Purpose: This indicator measures how fast the school age population is changing.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. It is critical for promoting sustainable development and
improving the capacity of people to participate in decision making to address their sustainable
development concerns.
Knowledge of the rate of change in the school-age population assists in planning for educational
facilities and services at the national and local levels. In most developing countries, growth in the
school-age population represents a major component of the increase in educational services. For
instance, in the least developed countries, between 1990 and 1995, the annual increase in numbers at
the primary and secondary-school ages averaged around 2.5 per cent; the number of enrolled students
must grow this rapidly merely to maintain enrolment ratios at their current levels. However, the schoolage population is not increasing in all countries. Fluctuations in the school-age population may produce
a need to adjust educational resources and infrastructure.
(c) Linkages to Other Indicators: This indicator has close linkages with other socioeconomic indicators
such as the population growth rate, the fertility rate, and net migration. The size of the school age
population provides the base (denominator) for calculation of school enrolment ratios. It could influence
education response indicators, such as the share of Gross Domestic product devoted to education.
(d) Targets: International agreements do not establish specific national or global targets for this
indicator.
(e) International Conventions and Agreements: Not applicable, see section 3d above.
4. Methodological Description and Underlying Definitions
The school-age population is generally defined in three age groups, ages 6-11, ages 12-17 and ages l823, which are used by the United Nations Educational, Scientific and Cultural Organization (UNESCO)
for comparative purposes, since they correspond to the main educational levels of many countries.
Other age groupings are used in some countries. The population figures should also be tabulated by
sex, as a basis for calculating gender-specific enrolment ratios.
The rate of change of the school-age population for a country is generally based on an intercensal
population growth rate calculated from two censuses, each adjusted for incompleteness and age misstatement. For periods following the most recent census, the changing numbers at each school age can
be estimated, first, by applying estimated survival rates to the adjusted numbers of persons enumerated
at the census. For dates more than 5 or 6 years since the census, account must be taken of children of
school age born since the census. Finally, it is necessary to estimate the amount of net migration, which
tends to be an important factor for smaller areas, even if it is unimportant at the national level. The
difficulty of estimating the components of population change make estimates of growth of the school-age
population increasingly subject to doubt as the time since the last population enumeration increases.
5. Assessment of the Availability of Data from International and National Sources
As indicated in section 4 above, the rate of change of population of school age can be calculated for
national and sub-national areas from census data. The United Nations recommends that countries take
censuses every 10 years, and these data can be used to calculate an intercensal population growth
rate. In recent decades most countries have carried out censuses; 204 countries or areas carried out a
census during the 1990 census decade (1985 to 1994).
National and sub-national census data are available by sex and age for the large majority of countries
from national sources (country publications) as well as from special country questionnaires sent to
national statistical offices from the Statistical Division of the United Nations Department of Economics
and Social Information and Policy Analysis (DESIPA). For all countries, national census data are
evaluated and, if necessary, adjusted for incompleteness by the Population Division, DESIPA as part of
its preparations of the official United Nations population estimates and projections. Past, current and
projected school age populations are prepared for all countries by the Population Division, and appear in
the United Nations publication, World Population Prospects: The 1994 Revision (see section 7 below).
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations Department for Economic and Social Information and Policy
Analysis (DESIPA). The contact point is the Director, Population Division, DESIPA; fax no. (1 212) 963
2147.
7. Further Information
Population Division, DESIPA, MORTPAK-LITE - The United Nations Software Package for
Mortality Measurement (United Nations, New York, 1988).
Population Division, DESIPA, The Sex and Age Distribution of the World Populations - the 1994
Revision (United Nations publication, Sales No. E.95.XIII.2, 1994).
Population Division, DESIPA, World Population Prospects: The 1994 Revision (United Nations
publication Sales No. E.95.XIII.16, New York, 1995).
Statistical Division, DESIPA, 1993 Demographic Yearbook (United Nations Sales No.
E/F.95.XIII.1, 1995).
UNESCO, Trends and Projections of Enrolment by Level of Education, by Age and by Sex,
1960-2025 (as assessed in 1993), CSR-E-63.
PRIMARY SCHOOL ENROLMENT RATIO - GROSS
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Primary
school
enrolment
ratio
gross.
(b) Brief Definition: Total enrolment in primary education as a proportion of the population of primary
school-age
according
to
national
regulations.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Driving Force.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The gross enrolment ratio is a general indicator of the level of participation in primary
education. It provides at the same time a measure of the availability and utilization of school places to
satisfy the educational needs of the eligible school-age population.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development and for effective
participation in decision making. It is during the primary educational stage when children become aware
of the basic knowledge and values regarding sustainable development.
This indicator is used in monitoring the general status and trends of participation in primary education,
and in assessing the relation between demand and supply of educational opportunities. Gross
enrolment ratios of less than 100% identify situations in which there is a need for more school places to
respond to unsatisfied educational needs, and/or for measures to encourage increase in enrolment.
When the indicator has a value in excess of 100, it highlights the incidence of under-aged and/or overaged enrolment. As regards over-aged students, their presence may be explained by late entrance or
the incidence of repetition.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
capacity building, information and science, and the role of the major groups. By including under-aged
and over-aged students, gross enrolment ratio can only provide broad indications of the level of
participation and school capacity utilization. For more precise assessments the net enrolment ratio
should be used which is however conditioned by the availability of data on enrolment by age.
(d) Targets: The value of gross enrolment ratios can vary from less than 10% to more than 100%,
reaching 130% in some countries when there are sizable under-aged and/or over-aged enrolment. For
countries with low gross enrolment ratios, the target is to reach and cross the 100% threshold. For those
posting 130 or 140% gross enrolment ratio, the target would be to lower it to 100%, by reducing in
particular over-aged enrolment and grade repetition.
(e) International Conventions and Agreements: The International Covenants on Human Rights and
Optional Protocol.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Gross enrolment ratio for primary education is the most
frequently used education indicator. By relating actual total enrolment in primary education, irrespective
of age, to the population who according to the prevailing national regulations should be enrolled, this
indicator of participation in primary education is conceptually simple as well as easy to derive. The lower
limit of the population age-group is the entrance age to primary education and the upper limit is obtained
by adding as many single ages as there are grades.
(b) Measurement Methods: The ratio is calculated as follows:
Total
enrolment
Population in age-group e x 100
in
primary
education
where e is the age-group of the population eligible to participate in primary education according to
national regulations. For sound measurement, the ratio must be supported by consistent data for gender
and area (such as rural/urban zones).
(c) The Indicator in the DSR Framework: This indicator stresses the importance of education to the
sustainable development process. It is recognized as a Driving Force indicator.
(d) Limitations of the Indicator: The gross enrolment ratio gives only broad indications of the
availability of school places and the level of participation in primary education. It is important to point out
that school age varies from country to country. The official entry age may not be adhered to by large
sectors of the population in many developing countries because of lack of funding.
(e) Alternative Definitions: If data on enrolment in primary education by age are available, net
enrolment ratio can be derived as a more precise alternative indicator of participation in education.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Total enrolment in primary education; and the
corresponding school-age population according to national regulations, classified by sex. The number of
school places available would provide additional meaning to this indicator.
(b) Data Availability: Data on total enrolment are normally available for most countries on an annual
basis, collected through national school censuses. The corresponding data on primary school-age
population are available only during national population censuses. Many national statistical offices
produce inter-censal estimates as well as projections. United Nations population estimates and
projections can also be obtained for most countries except for those with less than 150 000 inhabitants.
(c) Data Sources: Data on enrolment can be collected from the schools during school censuses
organized by national ministries of education. Data on primary school-age population can be either
derived from national population census results, or estimated and projected for the intervening years by
national statistical offices or by the United Nations Population Division, Department of Economics and
Social Information and Policy Analysis.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO, fax (33-1) 45 66 48 44.
7. Further Information
(a) Further Readings:
UNESCO, Statistical Yearbook (annual editions); World Education Report, editions 1991, 1993, 1995.
UNESCO, Paris.
(b) Other References:
UNESCO, Statistics of Education in Developing Countries - An Introduction to their Collection and
Analysis. Book 3. Division of Statistics, UNESCO, Paris 1983.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
PRIMARY SCHOOL ENROLMENT RATIO - NET
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Primary
school
enrolment
ratio
net.
(b) Brief Definition: This is the proportion of the population of the official age for primary education
according
to
national
regulations
who
are
enrolled
in
primary
schools.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Driving Force.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The net enrolment ratio provides a measure of the extent to which the population eligible
to participate in primary education is actually enrolled. By deduction, it can be used in gauging the size
of the non-enrolled primary school-age population.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development and for effective
participation in decision making. It is during the primary educational stage when children become aware
of the basic knowledge and values regarding sustainable development.
This indicator is used in monitoring the level of participation in primary education and in identifying the
non-enrolled school-age population. Net enrolment ratios approaching 100% indicate availability of
adequate primary school capacities and active enrolment of school-age children. Low net enrolment
ratios signal inadequacies in universalizing participation in primary education, due to either the lack of
school places or other factors that prevent children from enrolling in school. This indicator when
disaggregated by sex highlights the extent of gender disparities.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
capacity building, information and science, and the role of the major groups. By including under-aged
and over-aged students, gross enrolment ratio can only provide broad indications of the level of
participation and school capacity utilization. For more precise assessments the net enrolment ratio
should be used which is however conditioned by the availability of data on enrolment by age. Net
enrolment ratio is more precise than gross enrolment ratio for assessing the level of participation in
primary education. When combined in use with the latter, it provides an order of magnitude of the overaged and under-aged enrolment. If data on enrolment and population by single years of age are
available, the concept can be extended to derive age-specific enrolment ratios and school life
expectancy.
(d) Targets: At both the international and national levels, the target of primary education programmes is
to reach a 100% net enrolment ratio, or full participation in primary education of the school-age
population.
(e) International Conventions and Agreements: The International Covenants on Human Rights and
Optional Protocol; and the World Declaration on Education for All.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The basic for this indicator is well-known. The numerator for
the net enrolment ratio only includes those students enrolled in primary education whose ages are within
the nationally prescribed age-range for primary education. The denominator is the population of the
same official primary school-age.
(b) Measurement Methods: The ratio is calculated as follows:
Enrolment
within
the
Population in age-group e x 100
age-group
e
for
primary
education
where e is the age-group of the population eligible to participate in primary education according to
national regulations. As children enrolled within the age-range e may be a subset of the population of
the same age-range, the value of this ratio can only lie in the range from 0 to 100%.
(c) The Indicator in the DSR Framework: This indicator stresses the importance of education to the
sustainable development process. It is recognized as a Driving Force indicator.
(d) Limitations of the Indicator: The net enrolment ratio, compared to gross enrolment, is more
precise in measuring participation in education, but it also requires more basic data to derive the
indicator, namely: enrolment by age. However, these data are not collected by all countries, or may be
unreliable.
(e) Alternative Definitions: The net enrolment ratio can be further used to determine the size of the
non-enrolled school-age population, and over-aged and under-aged enrolment. If data on enrolment in
primary education by single years of age are available, age-specific enrolment ratios can also be
derived, as well as school life expectancy.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Data on enrolment in primary education and population
either by single years of age or corresponding to the official primary age-range, and classified by sex.
(b) Data Availability: Enrolment data are normally available for most countries on an annual basis,
collected through national school censuses. Some countries do not collect data on enrolment in primary
education by age, at least not on a regular basis. The corresponding data on primary school-age
population are available only during national population censuses or from inter-censal estimates. United
Nations estimates and projections can also be obtained for most countries except for those with less
than 150,000 inhabitants.
(c) Data Sources: Data on enrolment by age can either be collected from the schools during school
censuses organized by national ministries of education, or derived from data on school attendance by
age collected during population censuses. Data on primary school-age population can be derived from
national population census results, or estimated and projected for the intervening years either by the
national statistics office or by the United Nations Population Division, Department of Economics and
Social Information and Policy Analysis.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO, fax (33-1) 45 66 48 44.
7. Further Information
(a) Further Readings:
UNESCO Statistical Yearbook (annual editions); World Education Report, editions 1991, 1993, 1995.
UNESCO, Paris.
(b) Other References:
Statistics of Education in Developing Countries - An Introduction to their Collection and Analysis. Book
3. Division of Statistics, UNESCO, Paris 1983.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
SECONDARY SCHOOL ENROLMENT RATIO - GROSS
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Secondary
school
enrolment
ratio
gross.
(b) Brief Definition: Total enrolment in secondary education as a proportion of the population of
secondary
school-age
(c) Unit of Measurement: %.
according
to
national
regulations.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Driving Force.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The gross enrolment ratio is a general indicator of the level of participation in secondary
education. It provides at the same time a measure of the availability and utilization of school places to
satisfy the educational needs of the eligible school-age population.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development, and for effective
participation in decision making. It is during the secondary educational stage when more detailed
knowledge regarding sustainable development is gained, and its multiple interactions with environment,
society and the individual clarified.
This indicator is used in monitoring the general status and trends of participation in secondary
education, and assesses the relation between demand and supply of educational opportunities. Gross
enrolment ratios of less than 100% identify situations in which there is a need for more school places to
respond to unsatisfied educational needs, and/or for measures to encourage increase in enrolment.
When the indicator has a value in excess of 100, it highlights the incidence of under-aged and/or overaged enrolment. As regards over-aged students, their presence may be explained by late entrance into
secondary schools or the incidence of repetition.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
capacity building, information and science, and the role of major groups. By including under-aged and
over-aged students, gross enrolment ratio can only provide broad indications of the level of participation
in secondary education and school capacity utilization. For more precise assessments, the net
enrolment ratio should be used which is however conditioned by the availability of data on enrolment by
age.
(d) Targets: The value of gross enrolment ratios can vary from less than 10% to more than 100%,
reaching 110% in some countries when there are under-aged and/or over-aged enrolment. For countries
with low gross enrolment ratios, the target is to reach and cross the 100% threshold. For those posting
110% gross enrolment ratio, the target would be to lower it to 100%, by reducing in particular over-aged
enrolment and grade repetition.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: By relating actual total enrolment in secondary education,
irrespective of age, to the population who according to the prevailing national regulations should be
enrolled, this indicator of participation in secondary education is conceptually simple as well as easy to
derive.
(b) Measurement Methods: The ratio is calculated as follows:
Total
enrolment
Population in age-group e x 100
in
secondary
education
where e is the age-group of the population eligible to participate in secondary education according to
national regulations. For sound measurement; the ratio must be supported by consistent data for gender
and area (such as rural/urban zones).
(c) The Indicator in the DSR Framework: This indicator stresses the importance of education to the
sustainable development process. It is recognized as a Driving Force indicator.
(d) Limitations of the Indicator: The gross enrolment ratio gives only broad indications of the level of
participation in secondary education. There may be different stages and streams in secondary education
giving different degrees of emphasis on environment and sustainable development. These important
details that are not reflected in a general gross enrolment in secondary education. This indicator may
not capture the secondary education changes taking place in many countries, particularly with respect to
vocational education and second-chance programmes.
(e) Alternative Definitions: To meet the limitations expressed in 4d above, the use of participation
rates in secondary and tertiary education could be used as an alternative indicator. In the majority of
countries, secondary education is disaggregated into two stages. In many countries the end of the first
stage coincides with the end of compulsory education. This gross enrolment ratio may thus be adapted
and calculations derived to produce gross enrolment ratios by cycle for secondary education, when
appropriate.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Total enrolment in secondary education; and the
corresponding school-age population according to national regulations, classified by sex. The number of
school places available would provide additional meaning to this indicator.
(b) Data Availability: Data on total enrolment are normally available for most countries on an annual
basis, collected through national school censuses. The corresponding data on secondary school-age
population are available only during national population censuses or from inter-censal estimates. United
Nations population estimates and projections can be obtained for most countries except for those with
less than 150 000 inhabitants. For sound measurement, the ratio must be supported by consistent data
for gender and area (such as rural/urban zones).
(c) Data Sources: Data on enrolment can be collected from the schools during school censuses
organized by national ministries of education. Data on secondary school-age population can be either
derived from national population census results, or estimated and projected for the intervening years by
national statistical offices or by the United Nations Population Division, Department of Economics and
Social Information and Policy Analysis.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax (33-1) 45 66 48 44.
7. Further Information
(a) Further Readings:
UNESCO, Statistical Yearbook (annual editions); World Education Report, editions 1991, 1993, 1995.
UNESCO, Paris.
(b) Other References:
Statistics of Education in Developing Countries: An Introduction to their Collection and Analysis. Book 3.
Division of Statistics, UNESCO, Paris 1983.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
SECONDARY SCHOOL ENROLMENT RATIO - NET
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Secondary
school
enrolment
ratio
net.
(b) Brief Definition: This is the proportion of the population of the official age for secondary education
according to national regulations who are actually enrolled in secondary schools.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Driving Force.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The net enrolment ratio provides a measure of the extent to which the population eligible
to participate in secondary education is actually enrolled. By deduction, it can be used in gauging the
size of the non-enrolled secondary school-age population.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development, and for effective
participation in decision making. It is during the secondary educational stage when more detailed
knowledge regarding sustainable development is gained, and its multiple interactions with environment,
society and the individual clarified.
This indicator is used in monitoring the level of participation in secondary education and in identifying
the non-enrolled school-age population. Net enrolment ratios approaching 100% indicate availability of
adequate secondary school capacities and active enrolment of school-age youth. Low net enrolment
ratios signal inadequacies in ensuring full participation of the school-age population in secondary
education, either for the lack of school places or due to other factors that prevent young people from
enrolling in secondary schools. This indicator when disaggregated by sex highlights the extent of gender
disparities.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
capacity building, information and science, and the role of major groups. Net enrolment ratio is more
precise than gross enrolment ratio for assessing the level of participation in secondary education. When
combined in use with the latter, it could provide indications on the magnitude of over-aged and underaged enrolment. If data on enrolment and population by single years of age are available, the concept
can be extended to derive age-specific enrolment ratios and school life expectancy.
(d) Targets: At both the international and national levels, the target is to reach a 100% net enrolment
ratio, or full participation of the school-age population in secondary education.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The basis for this indicator is well known. The numerator for
the net enrolment ratio only includes those students enrolled in secondary education whose ages are
within the nationally prescribed age-range for secondary education. The denominator is the population
of the same official secondary school-age.
(b) Measurement Methods: The ratio is calculated as follows:
Enrolment
within
the
Population in the age-group e x
age-range
100
e
for
secondary
education
where e is the age-group of the population eligible to participate in secondary education according to
national regulations. As young persons enrolled within the age-range e may be a subset of the
population of the same age-range, the value of this ratio can only lie in the range of 0 to 100%.
(c) The Indicator in the DSR Framework: This indicator stresses the importance of education to the
sustainable development process. It is recognized as a Driving Force indicator.
(d) Limitations of the Indicator: The net enrolment ratio, compared to gross enrolment, may be more
precise for measuring participation in education, but it also requires more basic data to derive the
indicator namely: enrolment by age. In some countries these data are either not collected, or collected
but are not reliable.
(e) Alternative Definitions: In the majority of countries, secondary education is disaggregated into two
stages. In many countries the end of the first stage coincides with the end of compulsory education. The
net enrolment ratio may thus be adapted and calculations derived to produce net enrolment ratios by
cycle for secondary education, when appropriate.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Neededto Compile the Indicator: Data on enrolment in secondary education and population
either by single years of age or corresponding to the official secondary age-range, and by classified sex.
(b) Data Availability: Enrolment data are normally available for most countries on an annual basis,
collected through national school censuses. Some countries in the world do not collect data on
enrolment in secondary education by age, at least not on a regular basis. The corresponding data on
secondary school-age population are available only during national population censuses or from intercensal estimates. United Nations estimates and projections can be obtained for most countries except
for those with less than 150 000 inhabitants. For sound measurement, the ratio must be supported by
consistent data for gender and area (such as rural/urban zones).
(c) Data Sources: Data on enrolment by age can either be collected during school censuses organized
by national ministries of education, or derived from data on school attendance by age collected during
population censuses. Data on secondary school-age population can be derived from national population
census results, or estimated and projected for the intervening years either by the national statistics office
or by the United Nations Population Division, Department of Economics and Social Information and
Policy Analysis.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax (33-1) 45 66 48 44.
7. Further Information
(a) Further Readings:
UNESCO, Statistical Yearbook (annual editions); World Education Report, editions 1991, 1993, 1995.
UNESCO, Paris.
(b) Other References:
Statistics of Education in Developing Countries: An Introduction to their Collection and Analysis. Book 3.
Division of Statistics, UNESCO, Paris 1983.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
ADULT LITERACY RATE
Social
Chapter 36
Driving Force
1. Indicator
(a)
Name:
Adult
literacy
rate.
(b) Brief Definition: The proportion of the adult population aged 15 years and over which is literate.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Driving Force.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: In determining this indicator it provides a measure of the stock of literate persons within
the adult population. It reflects the accumulated accomplishment of education in spreading literacy. Any
shortfall in literacy would provide indications of efforts required in the future to extend literacy to the
remaining adult illiterate population.
(b) Relevance to Sustainable/Unsustainable Development: Literacy is critical for promoting and
communicating sustainable development and improving the capacity of people to address environment
and development issues. It facilitates the achievement of environmental and ethical awareness, values,
and skills consistent with sustainable development and effective public participation in decision making.
(c) Linkages to Other Indicators: Literacy is closely linked to indicators reflecting basic needs such as
education, capacity building, information and communication, and the role of major groups. The literacy
rate indicates the status, or stock of iterates at a given point in time. It is often linked to school enrolment
ratios and population reaching grade 5 of primary education, both of which influence the accumulation of
the stock of iterates.
(d) Targets: The general target is full literacy, i.e. 100% adult literacy rate. This is the goal of most
national efforts and international campaigns to eradicate illiteracy.
(e) International Conventions and Agreements: The World Declaration on Education for All to be
achieved by the year 2000.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The Revised Recommendation concerning the International
Standardization of Educational Statistics suggests the following definitions for statistical purposes:
i) A person is literate who can with understanding both read and write a short simple statement related
to his/her everyday life.
ii) A person is functionally literate who can engage in all those activities in which literacy is required for
effective functioning of his/her group and community and also for enabling him/her to continue to use
reading, writing and calculation for his/her own and the community's development.
Persons who do not fulfill (i) or (ii) are termed illiterates or functional illiterates respectively. Adult
literacy, in international practice, applies only to the population aged 15 years and over, classified by
sex, by five-year age-groups, and by urban/rural zones.
(b) Measurement Methods: To calculate the adult literacy rate, the number of iterates aged 15 years
and over is divided by the corresponding total population aged 15 years and over and multiplied by 100.
(c) The Indicator in the DSR Framework: Literacy is a reflection of the total education experience. It is
an essential element for effective participation in sustainable development processes, and represents a
Driving Force indicator within the DSR Framework.
(d) Limitations of the Indicator: As literacy is a relative concept, no single measure can separate the
literate from the illiterate. A cut-off point is not totally appropriate because there are many different forms
of literacy. A person might be literate in numeric terms, but have difficulty with comprehension. Literacy
can be defined in terms of work, school, home, and social spheres. Each area of life requires different
skills.
Therefore, literacy ideally should be determined by the measurement of reading, writing and numeracy
abilities of each person within a social context. It may however be too time-consuming, costly and
operationally complex to organize such measurements during national population censuses. Literacy
status is therefore usually based on self-declaration or declaration of the head of household, which
sometimes gives rise to concerns about data reliability and consequently comparability, especially for
females in many developing countries.
(e) Alternative Definitions: To meet the limitations discussed in 4d above, the definition of functional
literacy represents an alternative indicator. This is usually measured for four or five components of
literacy such as "prose", "document", and "quantitative" domains. The aim is to measure the degree of
functionality, rather than the dichotomy literate vs. illiterate.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Data on the number of iterates or illiterates and the
population aged 15 years and over as collected during population censuses and household surveys.
(b) Data Availability: Data are usually collected during national population censuses, or from household
surveys. Official statistics exist for most countries in the world but are often out-of-date due to late
census data release. The United Nations Educational, Scientific and Cultural Organization (UNESCO)
carries out periodical estimations and projections to fill data gaps. In principle literacy data are available
at both the national and sub-national levels. For sound measurement, the ratio must be supported by
consistent data for gender and area (such as rural/urban zones).
(c) Data Sources: The primary data sources are national population censuses and household surveys.
International data sources include the Statistical Division of the United nations Department of
Economics and Social Information and Policy Analysis (DESIPA); and UNESCO's Division of Statistics.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency for this indicator is the United Nations Educational, Scientific and
Cultural Organization (UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax
(33-1) 45 66 48 44.
(b) Other Organizations: The Statistical Division of DESIPA also collects statistics on literacy from
national population censuses and provide the data to UNESCO for processing and dissemination.
7. Further Information
UNESCO Statistical Yearbook (annual editions); Compendium of Statistics on Illiteracy: 1995 Edition. .
UNESCO, Paris. 1995.
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
CHILDREN REACHING GRADE 5 OF PRIMARY EDUCATION
Social
Chapter 36
State
1. Indicator
(a)
Name:
Children
reaching
grade
5
of
primary
education.
(b) Brief Definition: The estimated proportion of the population entering primary school who reach
grade
5.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State.
36:
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: This indicator provides an estimate of the proportion of children entering primary school
who reach grade 5 of primary education and thereby acquire basic literacy.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address environment and development issues. It
is also critical for achieving environmental and ethical awareness, values, and skills consistent with
sustainable development and effective public participation in decision making.
Policy makers concerned with children's retention in schools and their eventual acquisition of basic
literacy and numeracy skills would find this indicator particularly useful as it indicates the functioning, or
internal efficiency, of the education system and its ability to turn out literates. Appropriate policies and
measures could then be adopted to address problems of grade repetition and drop-out as well as
bottlenecks with regard to retention in school. Indirectly, this indicator reflects the quality and
performance of schools.
(c) Linkages to Other Indicators: Literacy is closely linked to indicators reflecting basic needs such as
education, capacity building, information and communications, and the role of major groups. Besides
assessing the functioning of the education system, this indicator is often used together with enrolment
ratios to depict respectively the complementary aspects of participation and retention in education. It can
be cross-referenced with adult literacy rate which reflects the cumulative output of the education system
over the years.
(d) Targets: With values that can vary from 0 to 100%, the general target would be 100%. This implies
complete retention of children in school to grade 5 (or zero drop-out).
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Efforts to extend literacy depend on the ability of the
education system to ensure full participation of school-age children and their successful progression to
reach at least grade 5, which is the stage when they are believed to have firmly acquired literacy and
numeracy. By estimating the percentage survival to grade 5, this indicator measures the proportion of
the population entering primary school who eventually reach grade 5.
(b) Measurement Methods: This indicator can be derived using the reconstructed cohort student flow
method, which is analogous to that used in demography to determine survival rates from one age to the
next. This method first derives the grade promotion, repetition and drop-out rates based on available
data on enrolment and repeaters by grade for two consecutive years using Markov chain calculations. It
then applies these rates to a cohort of 1,000 students in grade 1 to reconstruct their passage through
the education system assuming that these student flow rates by grade remain unchanged throughout
the life-time of the cohort. From the reconstructed cohort student flow, the percentage survival to grade
5 can be derived.
If pi, ri and di represent respectively promotion rate, repetition rate and drop-out rate at grade i of primary
education, they can be derived but the following conditions on the flow rates have to be satisfied:
pi + ri + di = 1
0 < pi, ri, di < 1
When these conditions are not satisfied, the method used to derive survival is no longer valid since it is
not possible to isolate the original cohort and any inferences made will be of a dubious nature.
A fundamental assumption is that the probability of the cohort entering primary school, irrespective of
the age of the pupils not reaching grade 5 is the same as that of the entrance age population for this
level of education. That is, the drop-out rate is the same for all pupils regardless of the age at which they
enter school.
(c) The Indicator in the DSR Framework: As explained in section 3c above, this indicator highlights
the functioning of the education system. As such it represents a State indicator within the DSR
Framework.
(d) Limitations of the Indicator: The measurement method described in 4b above is rather a
cumbersome one to administer. In addition, in some countries such as Germany and Austria the
concept of grade 5 does not exist in primary education. Data on enrolment and repetition by grade may
not be available for consecutive years for some countries and certain regions or schools within a
country. The reconstructed cohort student flow method assumes that promotion rates, repetition rates
and drop-out rates do not change from year to year. When applying this method to sub-national and
school levels, the derived drop-out rates by grade may sometimes present a negative value due to
transfers between schools. A suggested solution to this problem is to collect data on transferred
students by grade, and to deduct them from the corresponding enrolment figures before applying the
reconstructed cohort method.
(e) Alternative Definitions: In the absence of data on repeaters, the methodology outlined in section 4b
above may be adjusted by assuming that the repetition rate is 0. However, this assumption, in addition
to those described in 4 (b), presupposes that the repetition rates are quite low and that their magnitude
does not vary much between grades.
An alternative indicator for education effectiveness would be school drop-out rates, grade by grade.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Neededto Compile the Indicator: Basic data required to derive this indicator include:
enrolment and repeaters by grade for at least two consecutive years.
(b) Data Availability: Data on enrolment and repeaters by grade in primary school are general available
in most countries and also at sub-national and school levels. For sound measurement, this indicator
must be supported by consistent data for gender and area (such as rural/urban zones).
(c) Data Sources: Data on enrolment and repeaters by grade and new entrants by age are generally
those collected during school censuses conducted by national ministries of education.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO, fax (33 1) 45 66 48 44.
7. Further Information
(a) Further Readings:
Not available.
(b) Other References:
Not available.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation Concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
SCHOOL LIFE EXPECTANCY
Social
Chapter 36
State
1. Indicator
(a)
Name:
School
life
expectancy.
(b) Brief Definition: Estimated average number of years a student will remain enrolled in an
educational
institution.
(c) Unit of Measurement: Number of years.
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State.
36:
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The indicator provides an estimate of the expected number of years of education that a
child can expect to receive if enrolled at school. This indicator can be used to gauge the overall level of
development and performance of an education system, in terms of the average duration of participation
in education of every child enrolled in school.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development and for effective
participation in decision making. It is during the primary educational stage when children become aware
of the basic knowledge and values regarding sustainable development. It is believed that the longer a
young person can remain in the education system, the more he/she is likely to learn about sustainable
development and to form the right attitude conducive to its future implementation.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
and capacity buildings, information and science, and the role of major groups. This indicator is closely
related to the enrolment ratios by level of education.
(d) Targets: Higher school life expectancy generally implies more exposure to education. It is
increasingly suggested that school life expectancy should be at least 10 to 12 years corresponding to
the total duration of primary and secondary education. However, it should be underlined that this
indicator does not measure the number of grades completed but the number of years a student is
enrolled.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The school life expectancy is defined as the total number of
years of schooling which a child who is enrolled can expect to receive, assuming the probability of his or
her being enrolled in school at any particular future age is equal to the current enrolment ratio for that
age.
(b) Measurement Methods:
Eat
---
n
=
SLE
a=i
where
Pat
E
P
a
=
age;
a
=
i,
...n;
t = the year for which the indicator is derived
=
=
i
=
school
enrolment
population
starting
age
(c) The Indicator in the DSR Framework: The indicator focuses on the importance of education to the
sustainable development process. It represents a measure of the State of education within the DSR
framework.
(d) Limitations of the Indicator: This indicator requires data on enrolment and population by single
years of age, which certain countries have yet to collect on a systematic basis. The estimated number of
years enrolled does not necessarily reflect the number of grades of the regular educational system
completed. Besides, as it is based on cross-sectional data by level of education at a point in time rather
than on longitudinal time-series, it does not take into consideration differences among successive school
cohorts over time.
(e) Alternative Definitions: An alternative indicator for education effectiveness would be school dropout rates, grade by grade.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Enrolment and population by single years of age
corresponding to all levels of education.
(b) Data Availability: Data on enrolment and population by age are not available on a regular basis for
certain countries. Based on data from the population censuses, the Population Division of the United
Nations Department of Economics and Social Information and Policy Analysis (DESIPA) and certain
national statistical offices carry out estimations and projections of population by age. For sound
measurement, this indicator must be supported by consistent data for gender and area (such as
rural/urban zones).
(c) Data Sources: Data on enrolment by age can be obtained from the national ministries of education.
The source of the data on population by age can be either the national statistical offices or DESIPA. The
latter updates their estimates and projections every two years for countries with a population of more
than 150 000 in 1990.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax (33 1) 45 66 48 44.
7. Further Information
(a) Further Readings:
Not available.
(b) Other References:
Not available.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation Concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
DIFFERENCE BETWEEN MALE AND FEMALE SCHOOL ENROLMENT RATIOS
Social
Chapter 36
State
1. Indicator
(a)
Name:
Difference
between
male
and
female
school
enrolment.
(b) Brief Definition: The arithmetical difference between male and female enrolment ratios.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State.
36:
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: This indicator indicates the extent of gender disparities with regard to the degree of
participation in education between male and female.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development, and for effective
participation in decision making. Differences in educational participation between male and female draw
attention to the likely existence of gender disparities.
The relevance of this indicator in many developed countries is limited as primary school is compulsory
with an enrolment ratio of usually 100%. If the enrolment is lower it usually indicates a data problem.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
a capacity building, information and science, and the role of major groups. Differences between male
and female enrolment ratios can be calculated for primary and secondary education, and for gross and
net ratios. Such differences may also be applied to adult literacy rates and other indicators which are
derived by gender and expressed in terms of ratios or percentages. In practice, this indicator of gender
differences is to be presented and interpreted together with the corresponding indicators of enrolment
ratio by sex, so as to examine concurrently the overall level of participation in education for both sexes
as well as the degree of disparity between them.
(d) Targets: The value of this indicator can vary from +35% to -20% in countries for primary school
gross enrolment, with positive differences indicating higher educational participation for male than for
female, and negative differences showing the reverse. The target is for a balance where both male and
female have the same level of participation in education.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Various concepts exist for indicators or indices of gender
disparity (see section 4e below). The concept chosen here is based on the criteria of simplicity of
computation and interpretation as well as the discriminatory power of the indicator derived.
(b) Measurement Methods: This indicator is calculated by subtracting the enrolment ratio for female
from the corresponding enrolment ratio for male, i.e. ENRM - ENRF
(c) The Indicator in the DSR Framework: he indicator focuses on the importance of education to the
sustainable development process. It represents a measure of the State of education within the DSR
framework.
(d) Limitations of the Indicator: This indicator provides an idea of the magnitude of gender disparities
in the level of participation in education, based on enrolment ratios. As mentioned in section 3c above,
this indicator should be presented and interpreted together with the corresponding enrolment ratios so
as to give a more comprehensive picture of the extent of gender disparities in the light of the overall
level of educational participation.
(e) Alternative Definitions: Other indicators and indices of gender disparity include: (ENRM ENRF)/ENRM; (ENRM - ENRF)/ENRF; (ENRM - ENRF)/ENRMF; Gini coefficient; and the index of
gender disparity in the Human Development Report 1995 published by the United Nations Development
Programme.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Comple the Indicator: Enrolment by sex (and also by age in the case of net
enrolment ratio) and by level of education; and the corresponding school-age population according to
national regulations, classified by sex.
(b) Data Availability: Data on enrolment by sex, age and by level of education are normally available
for most countries on an annual basis, collected through national school censuses. The corresponding
data on primary school-age population are available only during national population censuses. Many
national statistical offices produce inter-censal estimates as well as projections. United Nations
population estimates and projections can also be obtained for most countries except for those with less
than 150 000 inhabitants.
(c) Data Sources: Data on enrolment can be collected from schools during school censuses organized
by national ministries of education. Data on primary school-age population can be either derived from
national population census results, or estimated and projected for the intervening years by the national
statistics office or by the Population Division of the United Nations Department of Economics and Social
Information and Policy Analysis.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax (33 1) 45 66 48 44.
7. Further Information
(a) Further Readings:
UNESCO, Statistical Yearbook (annual editions); World Education Report, editions 1991, 1993, 1995.
UNESCO, Paris.
(b) Other References:
UNESCO, Statistics of Education in Developing Countries - An Introduction to their Collection and
Analysis. Book 3. Division of Statistics, UNESCO, Paris 1983.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation Concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
WOMEN PER 100 MEN IN THE LABOUR FORCE
Social
Chapter 36
State
1. Indicator
(a)
Name:
Women
per
(b)
Brief
Definition:
Women
(c) Unit of Measurement: Number.
100
men
per
hundred
in
men
the
in
the
labour
labour
force.
force.
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State.
36:
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: The ratio measures men and women's respective shares in the labour force structure and
should not be confused with the participation rate.
(b) Relevance to Sustainable/Unsustainable Development: A small women's share, assuming
properly designed surveys, indicates non access to education and inequality of opportunity and
treatment, from, for examples, national laws or general social practices. Such situations are usually
accepted as unsustainable.
(c) Linkages to Other Indicators: This indicator is linked to others reflecting the role and participation
of women as a major societal group. It would be better interpreted by age group and according to the
number of children to be cared for; and paired with indicators on education and ratio of average female
wage to average male wage.
(d) Targets: Not available.
(e) International Conventions and Agreements: Equality of opportunity and treatment is a basic
international standard. International Labour Office (ILO) conventions No. 100, Equal Remuneration
Convention, 1951; No. 111 Discrimination Employment and Occupation Convention 1958; No. 156
Workers with Family Responsibilities Convention, 1981 are relevant to this indicator.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The current economically active population or labour force
has two components: the employed and the unemployed population. The international standard
definition established by the Thirteenth International Conference of Labour Statisticians (ILO, 1982) is
based on the following elements:
i) The survey population: This is defined as all usual residents (de jura population) or all persons present
in the country at the time of the survey (de facto population). Some particular groups, such as the armed
forces or other populations living in institutions, nomadic people, etc. may be excluded.
ii) An age limit: In countries where compulsory schooling and legislation on the minimum age for
admission to employment have broad coverage and are widely respected, the age specified in these
regulations may be used as a basis for determining an appropriate minimum age limit for measuring the
economically active population. In other countries, the minimum age limit should be determined
empirically on the basis of: (i) the extent and intensity of participation in economic activities by young
people; and (ii) the feasibility and cost of measuring such participation with acceptable accuracy. Some
countries use a maximum age limit as well, often linked to the most common age for pensions.
iii) The involvement in economic activities during the survey reference period: The concept of economic
activity adopted by the Thirteenth International Conference of Labour Statisticians (1982) is defined in
terms of contribution to the production of goods and services as set forth by the United Nations System
of National Accounts, revised in 1993.
iv) A short reference period: For example, one week or one day.
(b) Measurement Methods: The labour force is distributed by gender. Gender is a basic descriptive
variable in censuses or household/labour force sample surveys, questionnaires and administrative
records. The total number of women in the labour force is then divided by the total number of men in the
labour force and the result compared to 100.
(c) The Indicator in the DSR Framework: Equal participation of men and women in society is one of
the principles tenets of sustainable development. The ratio women per hundred men in the labour force
measures participation and is included as a State indicator within the DSR Framework; along with
population reaching grade 5 of primary education, and mean years of schooling. The corresponding
Driving Force indicators are the rate of growth of school age population; the primary school enrolment
ratio; secondary school enrolment ratio; and adult literacy rate. The remaining indicator, GDP spent on
education, is a Response indicator.
(d) Limitations of the Indicator: All the indicators in section 4c above relate to improving educational
attainment, and strongly suggest a direct link between an increased women's share in the labour force
and an higher educational level. This would make more sense for participation rates than for this ratio,
though various factors can affect both indicators, which shows only the relative share of both genders in
the labour force at a given moment. In addition, the indicator does not capture women's participation in
the informal or domestic sectors.
Estimates according to the international standards can in practice be made most reliably on the basis of
data collected through household surveys and population censuses. Some of the criteria specified in the
international standards can only be implemented precisely from personal interviews - data which is
expensive and time consuming to acquire. This is the only data source which, on a regular basis and
with an appropriate survey design, can cover virtually the entire population of a country, all branches of
economic activity, all sectors of the economy, all types of activity status and all categories of workers,
and allows joint and mutually exclusive measurement of the employed, unemployed and inactive
persons.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Activity status, gender. The relevance of the indicator
would be improved with the use of disaggregated area data, such as urban/rural zones.
(b) Data Availability: The availability of recent data is ascertained for 57 countries, 5 in Africa, 15 in
America, 13 in Asia, 22 in Europe, and 2 in Oceania. The sources are labour force sample surveys for
40 countries, household sample surveys for 6 countries, censuses for six countries and official estimates
for 5 countries.
(c) Data Sources: (i) population censuses and household sample surveys; (ii) establishment censuses
and establishment sample surveys; and (iii) various types of administrative records.
6. Agencies Involved in the Development of the Indicator
The lead agency is The International Labour Office (ILO) of the United Nations, located in Geneva. The
contact point is the Focal Point for Environment and Sustainable Development, ILO; fax no. (41 22) 798
8685.
7. Further Information
(a) Data:
Yearbook of Labour Statistics, ILO, Geneva.
Bulletin of Labour Statistics (quarterly) and its Supplement (January/February, April/May, July/August
and October/November), ILO, Geneva.
Statistical yearbooks and other publications issued by the national statistical offices.
(b) Methodology:
Surveys of Economically Active Population, Employment, Unemployment and Underemployment - An
ILO Manual on Concepts and Methods, ILO, Geneva, 1992.
Sources and Methods: Labour Statistics, Volumes 3 and 5, ILO, Geneva, 1991 and 1990, currently
updated.
System of National Accounts 1993, Commission of the European Communities, International Monetary
Fund, Organisation for Economic Co-operation and Development, United Nations, World Bank,
Brussels/Luxembourg, New York, Paris, Washington, D.C., 1993.
Current international recommendations on labour statistics, ILO, Geneva, 1988. See particularly the
resolution concerning Statistics of the Economically Active Population, Employment, Unemployment and
Underemployment adopted by the Thirteenth International Conference of Labour Statisticians, October
1982.
(c) International Conventions and Recommendations:
Labour Statistics Convention (No. 160) and Recommendation (No. 170), 1985.
Equal Remuneration Convention (No. 100) and Recommendation (No. 90), 1951.
Discrimination (Employment and Occupation) Convention (No. 111) and Recommendation (No. 111),
1958.
Workers with Family Responsibilities Convention (No. 156) and Recommendation (No. 165), 1981.
(d) Other Studies on Gender Issues:
Women Workers: An Annotated Bibliography, 1983-1994, ILO, Geneva, 1995, XIII, 290 pages
(International Labour Bibliography. No. 14). Produced from the LABORDOC database, lists 953 Englishlanguage publications, technical reports, working papers and other documents produced at ILO
headquarters or in ILO field offices, or prepared in connection with ILO programmes.
GROSS DOMESTIC PRODUCT SPENT ON EDUCATION
Social
Chapter 36
Response
1. Indicator
(a)
Name:
Gross
Domestic
Product
(GDP)
spent
on
(b) Brief Definition: Education expenditure expressed as a proportion
(c) Unit of Measurement: %.
education.
of GDP.
2. Placement in the Framework
(a) Agenda 21: Chapter 36:
(b) Type of Indicator: Response.
Promoting
Education,
Public
Awareness
and
Training.
3. Significance (Policy Relevance)
(a) Purpose: This indicator provides a measure of financial resource input into education and its share
of national revenue support. It enables better assessment of the adequacy and allocation of financial
resource allocated to education within the national economy. It facilitates appropriate policy and
decision-making, while taking into account investments in other public sectors.
(b) Relevance to Sustainable/Unsustainable Development: Education is a process by which human
beings and societies reach their fullest potential. Education is critical for promoting sustainable
development and improving the capacity of people to address their sustainable development concerns.
While basic education provides the underpinnings for any environmental and development education,
the latter needs to be incorporated as an essential part of learning. It is also critical for achieving
awareness, values, skills and behaviour consistent with sustainable development, and for effective
participation in decision making. Financial resources for education directly determines school capacity
and quality, which in turn influences enrolment, retention and learning of children and youth in school.
Relevance is increased if disaggregation to primary, secondary, and tertiary education is feasible.
(c) Linkages to Other Indicators: Education is closely linked to other indicators reflecting basic needs,
capacity building, information and science, and the role of major groups. This measure is also closely
linked to other GDP and expenditure indicators. The effect of expenditure on education can be verified
by changes in enrolment ratios and literacy rates. These ratios and rates in turn indicate shortfalls and
disparities which require modifications in the allocation of financial resource for education.
(d) Targets: There is no standard international target for GDP spent on education. A general target
referenced, but not sanctioned by international conventions or agreements, suggests that countries
should devote at least 5% of GDP to education.
(e) International Conventions and Agreements: See section 3d above.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: GDP spent on education has been in common use to
compare the level of financial resources for education among countries. The basic concept is to
measure the share of financial resource devoted to education from total national revenue.
(b) Measurement Methods: This indicator can be calculated as follows:
Total
expenditure
on
education
x
100
GDP
Total expenditure comprises both public and private expenditure.
(c) The Indicator in the DSR Framework: Adequate fiscal support for education is essential for
sustainable development. GDP spent on education represents a Response indicator within the DSR
framework.
(d) Limitations of the Indicator: The indicator does not capture effectiveness and efficiency in the
education system. It does not differentiate, for example, between education expenditure which is
relevant for a country's development compared to that which is not. International comparability of the
indicator is problematic: GDP spent on education can be affected by the availability and reliability of data
covering both public and private expenditure on education, particularly from households, productive and
service enterprises, local communities, NGOs, and individuals. Spending by non-government institutions
on education, for example, will be elusive to capture.
The indicator also has the following advantages: (i) inflationary and deflationary trends do not affect the
comparability of this ratio either over time or between countries since the data refer to the same year; (ii)
currency fluctuation does not impinge on the comparability of this ratio.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Capital and current expenditure on education in the
national currency covering both the public and private sectors; and GDP in the national currency.
(b) Data Availability: Data or estimates on GDP are generally available for all countries on an annual
basis, either from the national ministries of finance or the World Bank. Data on public expenditure on
education are usually collected either by the ministries of education, or finance; and/or national
statistical offices. Private education expenditures, particularly those made by households, enterprises,
local communities, NGOs and individuals are more difficult to obtain and may be very often incomplete.
(c) Data Sources: See section 5b above.
6. Agencies Involved in the Development of the Indicator
The lead agency for this indicator is the United Nations Educational, Scientific and Cultural Organization
(UNESCO). The contact point is the Director, Division of Statistics, UNESCO; fax (33 1) 45 66 48 44.
7. Further Information
(a) Further Readings:
Not available.
(b) Other References:
Not available.
(c) Status of the Methodology:
This indicator has the status of a recommendation since the basic data elements to derive it are
included in the Revised Recommendation Concerning the International Standardization of Education
Statistics adopted by the UNESCO General Conference at its twentieth session, Paris, 1978.
Chapter 6: Protecting and promoting human health












Basic sanitation: percent of population with adequate excreta disposal facilities
Access to safe drinking water
Life expectancy at birth
Adequate birth weight
Infant mortality rate
Maternal mortality rate
Nutritional status of children
Immunization against infectious childhood diseases
Contraceptive prevalence
Proportion of potentially hazardous chemicals monitored in food
National health expenditure devoted to local health care
Total national health expenditure related to GNP
Chapter 6: Protecting and promoting human health
BASIC SANITATION: PERCENT OF POPULATION WITH ADEQUATE EXCRETA DISPOSAL
FACILITIES
Social
1. Indicator
Chapter 6
State
(a) Name: Basic sanitation: percent of population with adequate excreta disposal facilities.
(b) Brief Definition: Proportion of population with access to a sanitary facility for human excreta
disposal
in
the
dwelling
or
immediate
vicinity.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
(b) Type of Indicator: State.
Chapter
6:
Protecting
and
Promoting
Health.
3. Significance (Policy Relevance)
(a) Purpose: To monitor progress in the accessibility of the population to sanitation facilities.
(b) Relevance to Sustainable/Unsustainable Development: This represents a basic indicator useful
for assessing sustainable development, especially human health. Accessibility to adequate excreta
disposal facilities is fundamental to decrease the faecal risk and the frequency of associated diseases.
Its association with other socioeconomic characteristics (education, income) and its contribution to
general hygiene and quality of life also make it a good universal indicator of human development. When
broken down by geographic (such as rural/urban zones) or social or economic criteria, it also provides
tangible evidence of inequities.
(c) Linkages to Other Indicators: The indicator is closely associated with other socioeconomic
indicators (see section 3b above), particularly the proportion of population with access to adequate and
safe drinking water. These indicators represent two of the eight elements of primary health care.
(d) Targets: International targets for this indicator have been established under the auspices of the
World Health Organization (WHO). The Global Strategy for Health and the more regent Ninth General
Programme provide targets of 100% by the year 2000 and 75% by the year 2001 respectively. In
addition, many countries have established national targets.
(e) International Conventions and Agreements: The International Drinking Water Supply and
Sanitation Decade (IDWSSD) 1980-1990 is an international agreement relevant to this indicator. It
represents a component of the WHO Global Strategy for Health for All by the year 2000.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Definitions for sanitary facility and population covered are
required.
i) Sanitary facility: "A sanitary facility is a unit for disposal of human excreta which isolates faeces from
contact with people, animals, crops and water sources. Suitable facilities range from simple but
protected pit latrines to flush toilets with sewerage. All facilities, to be effective, must be correctly
constructed and properly maintained".
ii) Population covered: This includes the urban population served by connections to public sewers; the
urban population served by household systems (pit privies, pour-flush latrines, septic tank, etc); the
urban population served by communal toilets; and the rural population with adequate excreta disposal
such as pit privies, pour-flush latrines, etc.
(b) Measurement Methods: This indicator may be calculated as follows: The numerator is the number
of people with adequate excreta-disposal facilities available multiplied by 100. The denominator is the
total population.
(c) The Indicator in the DSR Framework: Basic sanitation is a fundamental factor in the human health
component of sustainable development. This indicator reflects the State of access to sanitary facilities
with in the DSR Framework.
(d) Limitations of the Indicator: The availability of facilities does not always translate into their
utilization.
(e) Alternative Definitions: This indicator could also be expressed as the percent of people without
access to adequate sanitation. The population that must be used in the numerator is the number of
people without access to adequate sanitation. If the data available are in terms of proportion of
households for which sanitation is available, it should be possible to convert this into a percentage of
population, using average figures for household size. Also see section 4d above.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: The number of people with access to adequate sanitation,
and the total population.
(b) Data Availability: Routinely collected at the national and sub-national levels in most countries using
censuses and surveys.
(c) Data Sources: In order to arrive at more robust estimates of sanitation coverage, two main data
source types are required. First, administrative or infrastructure data which report on new and existing
facilities. Second, population-based data derived from some form of national household survey.
6. Agencies Involved in the Development of the Indicator
The lead agency is the World Health Organization (WHO). The contact point is the Director, Office of
Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
7. Further Information
(a) Further Readings:
WHO, Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva, WHO, 1981, p. 29.
WHO, Global Strategy for Health for All by the Year 2000. Geneva, WHO, 1981.
WHO, Ninth General Programme of Work Covering the Period 1996-2001. Geneva, WHO, 1994.
World Health Organization, Division of Operational Support in Environmental Health, October 1995.
(b) Other References:
World Health Organization. National and Global Monitoring of Water Supply and Sanitation. CWS Series
of Cooperative Action for the Decade, No. 2, 1982.
World Health Organization. Water Supply and Sanitation Sector Monitoring Report (WSSSMR), 1990.
ACCESS TO SAFE DRINKING WATER
Social
Chapter 6
State
1. Indicator
(a) Name: Percent of people with safe drinking water available in the home or with reasonable access.
(b) Brief Definition: Proportion of population with access to an adequate amount of safe drinking water
in a dwelling or located within a convenient distance from the user's dwelling.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
(b) Type of Indicator: State.
Chapter
6:
Protecting
and
Promoting
Health.
3. Significance (Policy Relevance)
(a) Purpose: To monitor progress in the accessibility of the population to safe drinking water.
(b) Relevance to Sustainable/Unsustainable Development: Accessibility to safe drinking water is of
fundamental significance to lowering the faecal risk and frequency of associated diseases. Its
association with other socioeconomic characteristics, including education and income, also makes it a
good universal indicator of human development. When broken down by geographic (such as rural/urban
zones), or social or economic criteria, it provides useful information on inequity.
(c) Linkages to Other Indicators: This indicator is closely associated with other socioeconomic
indicators on the proportion of people covered by adequate sanitation. These indicators are among the
eight elements of primary health care. It also has close links to other water indicators such as
withdrawals, reserves, consumption, or quality. (See section 3b above.)
(d) Targets: International targets for this indicator have been established under the auspices of the
World Health Organization (WHO). The Global Strategy for Health and the more regent Ninth General
Programme provide targets of 100% by the year 2000, and more than 85% by the year 2001
respectively. In addition, many countries have established national targets.
(e) International Conventions and Agreements: The International Drinking Water Supply and
Sanitation Decade (IDWSSD) 1980-1990 is an international agreement relevant to this indicator. It is a
component of the WHO Global Strategy for Health for All by the Year 2000.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: This indicator requires definitions for several elements.
i) Population covered: This includes urban population served by house connections, urban population
without house connections but with reasonable access to public stand posts, and rural population with
reasonable access to safe water.
ii) Reasonable access to water: This is defined as water supply in the home or within 15 minutes walking
distance. Actually a proper definition should be adopted taking the local conditions into account; in urban
areas, a distance of not more than 200 metres from a house to a public stand post may be considered
reasonable access. In rural areas, reasonable access implies that anyone does not have to spend a
disproportionate part of the day fetching water for the family's needs.
iii) Convenient distance: Convenient distance and access are distinct in a sense that there may be
access to water but it is not necessarily convenient to fetch the water due to distance. The water should
be within a reasonable distance from the home that is 200 metres.
iv) Adequate amount of water: The amount of water needed to satisfy metabolic, hygienic, and domestic
requirements. This is usually defined as twenty litres of safe water per person per day.
v) Safe water: The water does not contain biological or chemical agents at concentration levels directly
detrimental to health. "Safe water" includes treated surface waters and untreated but uncontaminated
water such as that from protected boreholes, springs, and sanitary wells. Untreated surface waters,
such as streams and lakes, should be considered safe only if the water quality is regularly monitored
and considered acceptable by public health officials.
(b) Measurement Methods: This indicator may be calculated as follows: The numerator is the number
of persons with access to an adequate amount of safe drinking water in a dwelling or located within a
convenient distance from the user's dwelling multiplied by 100. The denominator is the total population.
(c) The Indicator in the DSR Framework: Access to water is a crucial influence on human health and
sustainable development. The conditions related to water accessibility are contained within this State
indicator of the DSR Framework.
(d) Limitations of the Indicator: The existence of a water outlet within reasonable distance is often
used as a proxy for availability of safe water. The existence of a water outlet, however, is no guarantee
in itself that water will always be available or safe, or that people always use such sources.
(e) Alternative Definitions: This indicator may be also expressed as the percent of population without
access to sufficient and safe drinking water. Thus the population indicated in the numerator would be
those who do not have access to adequate and safe drinking water. If these data are available in terms
of the proportion of households, it should be possible to convert this into a percentage of the population,
using average figures for household size.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: The number of people with access to adequate and safe
water, and the total population. Data on the source of water, for example, house tap or yard pipe, would
provide additional meaning to this indicator.
(b) Data Availability: Routinely collected at the national and sub-national levels in most countries using
censuses and surveys.
(c) Data Sources: Two sources are common: administrative data that report on new and existing
facilities, and population data derived from some form of household survey or census.
6. Agencies Involved in the Development of the Indicator
The lead agency is the World Health Organization (WHO). The contact point is the Director, Office of
Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
7. Further Information
(a) Further Readings:
WHO, Global Strategy for Health for All by the Year 2000. Geneva, WHO, 1981.
WHO, Ninth General Programme of Work Covering the Period 1996-2001. Geneva, WHO, 1994.
WHO, Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva, WHO, 1981, p. 40.
(b) Other References:
World Health Organization. National and Global Monitoring of Water Supply and Sanitation. CWS Series
of Cooperative Action for the Decade, No. 2, 1982.
World Health Organization. Water Supply and Sanitation Sector Monitoring Report (WSSSMR), 1990.
Program of Action of the Ministerial Drinking Water Conference, 1994.
LIFE EXPECTANCY AT BIRTH
Social
Chapter 6
State
1. Indicator
(a)
Name:
Life
expectancy
at
birth.
(b) Brief Definition: The average number of years that a newborn could expect to live, if he or she were
to pass through life subject to the age-specific death rates of a given period.
(c) Unit of Measurement: Life expectancy at birth as expressed in years.
2. Placement in the Framework
(a)
Agenda
21:
Chapter
(b) Type of Indicator: State.
6:
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: Measures how many years on average a new-born baby is expected to live, given current
age-specific mortality risks. Life expectancy at birth is an indicator of mortality conditions and, by proxy,
of health conditions. It is also one of the most favoured indicators of social development, and is used as
one of the components of United Nations Development Programme's (UNDP) Human Development
Index.
(b) Relevance to Sustainable/Unsustainable Development: Mortality, with fertility and migration,
determines the size of human populations, their composition by age, sex, and ethnicity, and their
potential for future growth. Life expectancy, a basic indicator, is closely connected with health
conditions, which are in turn an integral part of development. The ICPD Programme of Action notes that
the unprecedented increase in human longevity reflects gains in public health and in access to primary
health-care services (paragraphs 8.1 and 8.2), which Agenda 21 recognizes as an integral part of
sustainable development and primary environmental care (paragraph 6.1). The ICPD Programme of
Action highlights the need to reduce disparities in mortality and morbidity among countries and between
socioeconomic and ethnic groups. It identifies the health effects of environmental degradation and
exposure to hazardous substances in the work-place as an issue of increasing concern.
(c) Linkages to Other Indicators: This indicator reflects many social, economic, and environmental
influences. It is closely related to other demographic variables, particularly the population growth rate. It
also has linkages with indicators of human health and the environment as well as economic indicators.
Examples of closely linked indicators would include infant mortality, and water and air quality.
(d) Targets: The Declaration of Alma Ata (1978) set a target of life expectancy greater than 60 years by
the year 2000, and the ICPD Programme of Action revised the target: life expectancy should be greater
than 65 years by 2005 and 70 years by 2015 for countries that currently have the highest levels of
mortality; and 70 years and 75 years, respectively, for the other countries (ICPD Programme of Action,
paragraph 8.5).
(e) International Conventions and Agreements: See section 3d above.
4. Methodological Description and Underlying Definitions
Calculation of life expectancy at birth is based on age-specific death rates, which may be calculated
separately for males and females, or for both sexes combined. The death rates are commonly tabulated
for ages 0 to 1 years, 1 to 5 years, and for 5-year age groups for ages 5 and above. Where data on
deaths by age are of good quality, or adjustments for age mis-statement and incompleteness can be
made, the life expectancy at birth can be calculated directly from registered deaths and population
counts, which are usually based on census enumerations, evaluated and, if necessary, adjusted.
Several steps are needed to derive life expectancy from age-specific death rates; the details can be
found in demographic or actuarial references that describe construction of life tables, for example,
Pressat (1972) or Shryock and Siegel (1980). For a description of the methodology that is linked to
computer routines to aid in the calculation, see MORTPAK-LITE (item 7, below).
When data on deaths by age are unavailable from registration systems or sample surveys, the life
expectancy at birth can be calculated through "indirect" methods based on special questions asked in
censuses or demographic surveys. For information on these indirect estimates, see Manual X and
MORTPAK-LITE (section 7, below).
5. Assessment of the Availability of Data from National and International Sources
Data is collected by the United Nations on a regular basis and available for most countries from vital
registration systems or surveys. For all countries, census and registration data are evaluated and, if
necessary, adjusted for incompleteness by the Population Division, United Nations Department of
Economics and Social Information and Policy Analysis (DESIPA) as part of its preparations of the official
United Nations population estimates and projections. Past, current and projected estimates of life
expectancy at birth are prepared for all countries by the Population Division, DESIPA and appear in the
United Nations publication, World Population Prospects: The 1994 Revision (see section 7, below).
Most countries tabulate data from death registration systems at the sub-national level. The infant
mortality rate and the crude death rate (annual number of deaths per thousand population) is more
readily available for sub-national units than is life expectancy at birth.
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations DESIPA. The contact point is the Director, Population
Division, DESIPA; fax no. (1 212) 963 2147. At the World Health Organization, the contact person is the
Director, Office of Global and Integrated Environmental Health; fax no. (41 22) 791 4123.
7. Further Information
DESIPA. World Population Prospects: The 1994 Revision. Population Division. United Nations Sales
No. E.95.XIII.16, New York, 1995.
DESIPA. Manual X: Indirect Techniques for Demographic Estimation. Population Division United
Nations Sales No. E.83.XIII.2, New York, 1983.
DESIPA. MORTPAK-LITE - The United Nations Software Package for Mortality Measurement.
Population Division. United Nations, New York, 1988.
DESIPA. Demographic Yearbook. Statistical Division. United Nations Sales No.E/F.95.XIII.1,1995.
1993.
Pressat, R. Demographic Analysis: Methods, Results, Applications. London, Edward Arnold; Chicago,
Aldine Atherton. 1972.
United Nations. Report of the International Conference on Population and Development. Programme of
Action of the International Conference on Population and Development. United Nations Document
A/CONF. 171/13. Cairo, Egypt, September 5-13, 1994.
Shryock, H.S, and J.S.Siegel. The Methods and Materials of Demography. U.S. Government Printing
Office, Washington, D.C. 1980.
ADEQUATE BIRTH WEIGHT
Social
Chapter 6
State
1. Indicator
(a)
Name:
Adequate
birth
weight.
(b) Brief Definition: Adequate birth weight is defined as equal or greater than 2500 grams, the
measurement being taken preferably within the first hours of life, before significant postnatal weight loss
has
occurred.
(c) Unit of Measurement: The indicator is expressed as the number of children per 1000 live births
whose birth weight is equal or greater than 2500 grams.
2. Placement in the Framework
(a)
Agenda
21:
(b) Type of Indicator: State.
Chapter
6:
Adequate
birth
weight.
3. Significance (Policy Relevance)
(a) Purpose: To monitor the percentage of underweight newborns in a community.
(b) Relevance to Sustainable/Unsustainable Development: Birth weight can be an important
indicator of community nutrition. Low birth weights signal insufficient access to adequate food supply. It
may also be related to certain diseases such as malaria, and to specific nutritional deficiencies such as
endemic goitre.
(c) Linkages to Other Indicators: This indicator is closely associated with nutrition related indicators
such as measure of weight-for-age and height-for-age for infants and children. Linkages to other health
and socioeconomic indicators are also pertinent.
(d) Targets: An international target for this indicator has been established by the World Health
Organization (WHO). Its Global Strategy for Health establishes a target of at least 90% of newborn
infants with a birth weight of at least 2500 grams. National standards are also significant and relevant to
countries and sub-national areas.
(e) International Conventions and Agreements: WHO's Global Strategy for Health for All by the Year
2000 is an international agreement relevant to this indicator.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Not available.
(b) Measurement Methods: In practice the percentage of low birth weight is first calculated as follows:
the numerator is represented by live born babies with birth weight less than 2500 grams multiplied by
100. The denominator is the total number of live born babies weighed. This percentage is then
subtracted from 100 to give the percentage of newborns weighing at least 2500 grams.
(c) The Indicator in the DSR Framework: This proxy measure may be considered as a State indicator
of human health and nutrition.
(d) Limitations of the Indicator: It may be difficult to obtain data on birth weight. This would apply, for
example, where coverage of supervised births by trained personnel is low.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Number of newborns with a birth weight less than 2500g.
Number of newborns weighed.
(b) Data Availability: In principle, routinely collected by ministries of health at the national and subnational levels in most countries.
(c) Data Sources: Sources of data would include ministries of health, health centres, hospital records,
sample surveys and/or special studies.
6. Agencies Involved in the Development of the Indicator
The lead agency is the World Health Organization (WHO). The contact point is the Director, Office of
Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
7. Further Information
Not available.
INFANT MORTALITY RATE
Social
Chapter 6
State
1. Indicator
(a) Name: Infant mortality rate (IMR).
(b) Brief Definition: The number of deaths under 1 year of age during a period of time per 1000 livebirths during the same period.
(c) Unit of Measurement: Rate per thousand live born.
2. Placement in the Framework
(a) Agenda 21: Chapter 6: Protecting and Promoting Human Health.
(b) Type of Indicator: State.
3. Significance (Policy Relevance)
(a) Purpose: The purpose of this indicator is to estimate the proportion of newborn who die during the
first year of life.
(b) Relevance to Sustainable/Unsustainable Development: Beyond its obvious relevance to policy
making for healthy children, the IMR is sensitive indicator of availability, utilization and quality of health
care, particularly perinatal care. Moreover, given its association with GNP per capita, family income,
family size, mothers' education, and nutrition, it is also considered one of the best indicators of overall
socioeconomic development of a community.
(c) Linkages to Other Indicators: This indicator, associated with access to perinatal health services, is
closely linked with life expectancy at birth. It is more generally linked to many other social and economic
indicators, including those listed in section 3b above.
(d) Targets: The Declaration of Alma Ata (1978) set a target for the IMR to be less than 50 per 1000
live-births by the year 2000. The Global Strategy for Health for All by the Year 2000 (WHO, 1981) aimed
to achieve IMR in all identifiable subgroups below 50 per 1000 live-births by the year 2000. The 1990
World Summit for Children Programme of Action adopted a target of reducing the 1990 infant mortality
rates by one third, or to 50 per 1000 live births, whichever is less, by the year 2000. The Programme of
Action of the International Conference on Population and Development further encouraged countries
with intermediate mortality levels to achieve an infant mortality rate below 50 deaths per 1000 births by
the year 2005, and all countries to achieve an infant mortality rate below 35 per 1000 live births by 2015.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Not available.
(b) Measurement Methods: Infant mortality rate is calculated by dividing the number of deaths under
one year of age in a given period of time x 1000 by the number of live-births in the same period of time.
(c) The Indicator in the DSR Framework: IMR provides a basic reflection of the overall socioeconomic
development in a country. It is a State indicator within the DSR Framework..
(d) Limitations of the Indicator: There are often problems in collecting the information required for
calculating the IMR in many less developed countries where routine data collection in the health
services omits many infant deaths. In countries where civil registration of deaths is incomplete,
especially in rural areas, many infants dying during the first weeks of life have not even been registered
as having been born. For this reason, rates based on civil registration in these countries, or hospital data
covering mainly urban areas, are biased to reflect the more privileged in the population. To compound
these problems, definitions of live birth differ among countries.
Where data on infant deaths and births are complete, or adjustments for age mis-statement and
incompleteness can be made, the infant mortality rate can be calculated directly. When such data are
unavailable from registration systems or maternity history data in sample surveys, the infant mortality
rate can be calculated through indirect or modelling methods based on special questions asked in
censuses or demographic surveys. For information on these estimates, see the Manual X and
MORTPAK-LITE (5) references listed in section 7 below.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Number of live births during a given period and number of
infant deaths during the same period. Disaggregated data by ethnicity or urban/rural zones support the
interpretation of this indicator.
(b) Data Availability: Data are now available for most countries thanks to special surveys of
representative samples of the population whenever vital registration systems are not available. Surveys
that rely on maternity histories, in which women are asked to give the date of birth and age of death (if
applicable) of each live-born child, are used in many household surveys, but care must be taken to
avoid age mis-reporting and to ensure that there is a complete report of infant deaths. The preceding
birth technique, used in antenatal clinics, maternity clinics, and at the time of immunization, can provide
a useful recent estimate of the probability of dying by age 2, for children of health service users at the
local level. Retrospective questions about the survival of all children born included in censuses and
surveys, and analyses using indirect estimation procedures, are also considered to be reliable sources.
(c) Data Sources: Original data sources include: vital registrations, sample registration systems,
surveillance systems, censuses, and demographic surveys. Information needed for this indicator is
collected by the United Nations on a regular basis. For all countries, survey and registration data are
evaluated and, if necessary, adjusted for incompleteness by the Population Division, Department of
Economics and Social Information and Policy Analysis (DESIPA) as part of its preparations of the official
United Nations population estimates and projections. Past, current and projected estimates of infant
mortality are prepared for all countries by the Population Division; DESIPA and appear in the United
Nations publication, World Population Prospects: The 1994 Revision. Demographic monitoring done by
government statistical offices often allows desegregation of information to show differences within
countries. Surveys are generally designed to provide estimates for major regions within countries as well
as at the national level.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agencies for this indicator are: the United Nations Department of Economics
and Social Information and Policy Analysis with the contact point being the Director, Population Division,
fax no. (1 212) 963 2147; and the World Health Organization (WHO) with the contact point being the
Director, Office of Global and Integrated Environmental Health, fax no. (41 22) 791 4123.
(b) Other Organizations: Other contributing organizations include: the United Nations Statistics
Division; and the United Nations Childrens Fund (UNICEF).
7. Further Information
(a) Further Readings:
WHO. Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva, 1981, p. 67.
WHO. Global Health for All Data Base. Geneva, 1994.
WHO. Global Strategy for Health for All by the Year 2000. Geneva, 1981.
DESIPA. Manual X: Indirect Techniques for Demographic Estimation. Population Division. United
Nations Sales No. E. 83.XIII.2, New York, 1983.
DESIPA. MORTPAK-LITE - The United Nations Software Package for Mortality Measurement.
Population Division. United Nations, New York, 1988.
DESIPA. World Population Prospects: The 1994 Revision. Population Division. United Nations Sales
No. E.95.XIII.16, New York, 1995.
United Nations. Report of the International Conference on Population and Development, Programme of
Action of the International Conference on Population and Development, Cairo, Egypt, September 5-13,
1994. United Nations Document A/CONF. 171/13.
UNICEF. State of the World Children. 1994.
(b) Other References:
Hill K. Approaches to the measurement of childhood mortality: A comparative review. Population Index
57(3):368-382, Fall, 1991.
WHO and UNICEF. Measurement of overall and cause-specific mortality in infants and children. Report
of a Joint WHO/UNICEF Consultation, 15-17 December 1992. Unpublished document
WHO/ESM/UNICEF/CONS/92.5.
DESIPA. 1993 Demographic Yearbook. Statistical Division. United Nations Sales No. E/F.95.XIII.1,
1995.
MATERNAL MORTALITY RATE
Social
Chapter 6
State
1. Indicator
(a)
Name:
Maternal
mortality
rate
(MMR).
(b) Brief Definition: Number of maternal deaths per 1 000 (or per 10 000 or per 100 000) live births.
(c) Unit of Measurement: Ratio. Due to the considerable decrease of MMR in many countries, this ratio
is now increasingly expressed per 10 000 or more often per 100 000 live-births, which is acceptable if
preferred and indicated by the country.
2. Placement in the Framework
(a)
Agenda
21:
Chapter
(b) Type of Indicator: State.
6:
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: This indicator estimates the proportion of pregnant women who die from causes related to
or aggravated by the pregnancy or its management.
(b) Relevance to Sustainable/Unsustainable Development: The MMR reflects the risk to mothers
during pregnancy and childbirth and is influenced by the following factors: general socioeconomic
conditions; unsatisfactory health conditions preceding the pregnancy; incidence of the various
complications of pregnancy and childbirth; availability and utilization of health care facilities, including
prenatal and obstetric care.
Monitoring MMRs is particularly useful for policy making and decisions regarding the accessibility to and
the quality of prenatal and obstetric care.
(c) Linkages to Other Indicators: This indicator is closely linked with infant mortality rate, contraceptive
prevalence, and health care expenditures.
(d) Targets: The Ninth General Programme of Work Covering the Period 1996-2001 calls for a
reduction of MMR by half in all countries between 1990 and the year 2000.
(e) International Conventions and Agreements: See section 3d above.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Maternal death: The death of a woman while pregnant or
within 42 days of termination of pregnancy, irrespective of the duration and the site of pregnancy, from
any cause related to or aggravated by the pregnancy or its management, but not from accidental or
incidental cause. Maternal deaths should be divided into two groups: (i) direct obstetric deaths are those
resulting from obstetric complications of the pregnant state (pregnancy, labour, and puerperium), from
interventions, omissions, incorrect treatment, or from a chain of events resulting from the above; and (ii)
indirect obstetric deaths are those resulting from previous existing disease or disease that developed
during pregnancy and which was not due to direct obstetric causes, but was aggravated by physiologic
effects of pregnancy.
The ICD-10 includes two further definitions of maternal mortality: (i) late maternal death: the death of a
woman from direct or indirect obstetric causes more than 42 days but less than one year after
termination of pregnancy; and (ii) pregnancy-related death: the death of a woman while pregnant or
within 42 days of termination of pregnancy, irrespective of the cause of death (includes deaths from
accidents).
(b) Measurement Methods: The maternal mortality ratio is expressed as follows:
Maternal
deaths
(direct
and
indirect)
x
K
live-births
k = 1 000, 10 000, or 100 000
For the purpose of international reporting of maternal mortality, only those maternal deaths occurring
before the end of the 42-day reference period should be included in the calculation of the rate, although
the recording of later maternal deaths is useful for national analytical purposes (see section 4e below).
Published maternal mortality rates should always specify the numerator (number of recorded maternal
deaths), which can be given as: (i) the number of recorded direct obstetric deaths; or the number of
recorded obstetric deaths (direct plus indirect). It should be noted that maternal deaths from HIV disease
and obstetrical tetanus are to be included in the MMR.
(c) The Indicator in the DSR Framework: The MMR provides an indication of the State of health care
and general socioeconomic conditions in a country.
(d) Limitations of the Indicator: The computation of the MMR implies a well-developed registration
system of births and deaths, as well as of causes of death. In order to improve the quality of maternal
mortality data and provide alternative methods of collecting data on deaths during pregnancy or related
to it, as well as to encourage the recording of deaths from obstetric causes occurring more than 42 days
following termination of pregnancy, the Forty-third World Health Assembly in 1990 adopted the
recommendation that countries consider the inclusion on death certificates of questions regarding
current pregnancy and pregnancy within one year preceding death. In the absence of a reliable
registration system, a proxy measurement may be used based on a count of deaths among women
soon after childbirth. To be used as a health indicator, the rate should preferably be based on
observations of at least 50 maternal deaths.
In countries with a small population (for example, less than half a million), and also in some larger
countries with very low maternal mortality, the rate should be considered with great caution, as annual
rates are subject to considerable random variation.
(e) Alternative Definitions: Recording "late maternal death" and monitoring its rate become more
important the more developed the country is. In either cases, it is essential to state which definition is
used. The definition of "pregnancy-related death" (see section 4a above) is irrespective of cause of
death and therefore includes incidental and accidental causes. This avoids the determination of
pathogenic causes of death, and strong clinical inputs during data collection. In countries where
maternal mortality is high, the bias introduced by the inclusion of external causes is usually low and
simplifies data collection.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Number of live births; number of maternal deaths.
(b) Data Availability: Data are routinely collected at national and sub-national levels in most countries.
(c) Data Sources: The primary sources of data are: vital statistics registration; and community-based
information (reproductive age mortality survey, case finding, sisterhood method). Hospital maternal
mortality ratios should not be interpreted as it is impossible to know the direction of the bias.
6. Agencies Involved in the Development of the Indicator
The lead agency is the World Health Organization (WHO). The contact point is the Director, Office of
Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
7. Further Information
(a) Further Readings:
Abouzahr, C. and Royston, E. Maternal Mortality: A Global Factbook. Geneva, WHO, 1991.
WHO. Maternal mortality, Rates and Ratios. A Tabulation of Available Information. 3rd ed. Geneva,
WHO/MCH/MSM/91.6, 1991.
WHO. Indicators to Monitor Maternal Health Goals. Report of a Technical Working Group. Geneva,
WHO, 1994.
(b) Other References:
WHO. Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva, WHO, 1981.
WHO. International Statistical Classification of Diseases and Related Health Problems, 10th rev.
Geneva, WHO, 1992.
WHO. Ninth General Programme of Work Covering the Period 1996-2001. Geneva, WHO, 1994.
WHO. Global Health for All Database. Geneva, WHO, 1994.
NUTRITIONAL STATUS OF CHILDREN
Social
Chapter 6
State
1. Indicator
(a) Name: The nutritional status of children in relation to national standards.
(b) Brief Definition: Children under age five whose weight-for-age and height-for-age is between either
80% and 120% of the reference value of the country, or within two standard deviations of this value.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
(b) Type of Indicator: State.
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: The purpose of this indicator is to measure long term nutritional imbalance and
malnutrition, as well as current under-nutrition.
(b) Relevance to Sustainable/Unsustainable Development: Health and development are intimately
interconnected. Meeting primary health care needs and the nutritional requirement of children are
fundamental to the achievement of sustainable development. Anthropometric measurements to assess
growth and development, particularly in young children, are the most widely used indicators of nutritional
status in a community. The percentage of low height-for-age reflects the cumulative effects of undernutrition and infections since birth, and even before birth. This measure, therefore, should be interpreted
as an indication of poor environmental conditions and/or early malnutrition. The percentage of low
weight-for-age reflects both the cumulative effects of episodes of malnutrition or chronic under-nutrition
since birth and current under-nutrition. Thus, it is a composite indicator which is more difficult to
interpret.
(c) Linkages to Other Indicators: This indicator is closely linked with adequate birth weight. It is also
associated with such socioeconomic and environmental indicators as squared poverty gap index,
access to safe drinking water, infant mortality rate, life expectancy at birth, national health expenditure
devoted to local health care, Gross Domestic Product (GDP) per capita, environmental protection
expenditures as a percent of GDP, and waste water treatment coverage.
(d) Targets: At least 90% of children within a population should have a weight-for-age that corresponds
to the reference values given in section 1b above by the year 2000. This target has been established by
the World Health Organization's (WHO) Global Strategy for Health for All by the Year 2000.
(e) International Conventions and Agreements: The WHO Global Strategy for Health for All by the
Year 2000 and its Ninth General Programme of Work, together with the United Nations World Summit
for Children represent international agreements relevant to this indicator.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: A national or international reference population is used to
calculate the indicators for weight-for-age and height-for-age. A WHO Working Group has
recommended that the best available data for this has been established by the United States National
Center for Health Statistics (see references in section 7 below). This data may be used for children up to
five years of age, since the influence of ethnic or genetic factors on young children is considered
insignificant.
Low weight and low height are defined as less than the value corresponding to two standard deviations
below the median of the respective frequency distributions for healthy children (see WHO, 1981 in
section 7 below).
(b) Measurement Methods: The proportion of children under five with acceptable weight-for-age (or
height-for-age) can be calculated by using the following formula:
Numerator:
number of children
acceptable x 100.
under
five
with
weight-for-age
(or
height-for-age)
Denominator: total number of children under five weighed.
For height, supine length is measured in children under two, and stature height in older children.
(c) The Indicator in the DSR Framework: This indicator, as a proxy measure for access to adequate
food supply, is a State indicator within the DSR Framework.
(d) Limitations of the Indicator: Available data may be outdated, site-specific, and lack a time series
perspective. In some countries, the age of children is difficult to determine. It is also difficult to measure
the height of children under two with accuracy and consistency.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: The data needed to compile this indicator are the number
of children under five weighed; and the number of children under five with weight-for-age or height-forage within the national reference values.
(b) Data Availability: The data are routinely collected by ministries of health at the national and
subnational levels for most countries.
(c) Data Sources: The primary national sources of data are the ministries of health.
6. Agencies Involved in the Development of the Indicator
The lead agency for the development of this indicator is the World Health Organization (WHO). At WHO,
the contact point is the Director, Office of Global and Integrated Environmental Health; fax no. (41 22)
791 4123.
7. Further Information
United States Department of Health, Education, and Welfare. Growth Charts. National Center for Health
Statistics, Public Health Service, Health Resources Administration. Rockville, Maryland. 1976.
Waterlow, J.C. et al. The Presentation and Use of Height and Weight Data for Comparing the Nutritional
Status of Groups of Children under the Age of Ten Years. Bulletin of the World Health Organization,
Volume 55: 489-498. 1977.
WHO. Global Strategy for Health for All by the Year 2000. Geneva. 1981.
WHO. Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva. 1981.
WHO. Ninth General Programme of Work Covering the Period 1996-2001. Geneva. 1994.
IMMUNIZATION AGAINST INFECTIOUS CHILDHOOD DISEASES
Social
Chapter 6
Response
1. Indicator
(a) Name: The percent of the eligible population that have been immunized according to national
immunization
policies.
(b) Brief Definition: The definition includes three components: (i) the proportion of children immunized
against diphtheria, pertussis, tetanus, measles, poliomyelitis, tuberculosis and hepatitis B before their
first birthday; (ii) the proportion of children immunized against yellow fever in affected countries of Africa;
and (iii) the proportion of women of child-bearing age immunized against tetanus.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21: Chapter
6:
(b) Type of Indicator: Response.
Immunization
against
infections
childhood
diseases.
3. Significance (Policy Relevance)
(a) Purpose: This indicator monitors the implementation of immunization programs.
(b) Relevance to Sustainable/Unsustainable Development: Health and sustainable development are
intimately interconnected. Both insufficient and inappropriate development can lead to severe health
problems in both developing and developed countries. Addressing primary health needs is integral to
the achievement of sustainable development. Particularly relevant is the provision of preventative
programmes aimed at controlling communicable diseases and protecting vulnerable groups. Good
management of immunization programmes, essential to the reduction of morbidity and mortality from
major childhood infectious diseases, is a basic measure of government commitment to preventative
health services.
(c) Linkages to Other Indicators: This indicator is linked to other health indicators, particularly those
associated with the young, such as infant mortality and life expectancy. It is influenced by such
indicators as health expenditure and the proportion of population in urban areas.
(d) Targets: Several international targets have been established for this indicator. In the Global Strategy
for Health and the Ninth General Programme at Work, all children and 90% of children respectively,
should be immunized against diphtheria, pertussis, tetanus, measles, poliomyelitis, and tuberculosis
(see section 7 below). The 1992 World Health Assembly agreed that all children should be immunized
against hepatitis B as part of expanded national programmes of immunization. In addition, all children in
affected countries of Africa should be immunized against yellow fever. At the World Summit for Children
it was resolved that all pregnant women should be immunized against tetanus.
(e) International Conventions and Agreements: See sections 3d and 7.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: A child is considered adequately immunized against a
disease when he or she has received the following number of doses: tuberculosis (1 dose); diphtheria,
pertussis, and tetanus (DPT) (2 or 3 doses according to the immunization scheme adopted in the
country); poliomyelitis (3 doses of live or killed vaccine); measles (1 dose); hepatitis B (3 doses); and
yellow fever (1 dose). A pregnant woman is considered adequately immunized against tetanus if she
has received at least 2 doses of tetanus toxoid during pregnancy or was already previously immunized.
(b) Measurement Methods:
i) Infant population: The numerator is the number of infants fully immunized with the specified vaccines x
100, while the denominator is the number of infants surviving to age one. If the national schedule
provides for immunization in a different age group, such as measles in the second year of age, the value
should be the percentage of children immunized in the target age group. For the proper management of
immunization programmes, it is however essential to be able to break down the data in such a way as to
show the percentage covered in the first year of life (or second year for measles immunization).
ii) Women of child-bearing age: The numerator is the number of women immunized with two or more
doses of tetanus toxoid during pregnancy x 100, while the denominator is the number of live births.
(c) The Indicator in the DSR Framework: This indicator focuses on a fundamental aspect of
preventative health care. As such, it represents a Response indicator influencing the State indicators of
health in the DSR Framework.
(d) Limitations of the Indicator: It is useful to have a composite indicator of adequate coverage by
immunization. However, it is easier to collect data on the global coverage of a population against one
disease than on the immunization of each child against all target diseases at the same time. This is why
in most countries only the former data are easily available and collected.
The percent of pregnant women immunized with two or more doses of tetanus toxoid during pregnancy
is rather easy to monitor through routine data collection in the health services. However, it
underestimates the percent of pregnant women actually immunized against tetanus. It does not tale into
account women who are already adequately immunized when becoming pregnant and therefore do not
require new doses of tetanus toxoid during pregnancy. Women in this category are not numerous in
countries where neonatal tetanus is still an issue and where, accordingly, this indicator is mainly used.
But in some countries in transition, with long-standing child immunization programmes, the percent of
pregnant women receiving tetanus toxoid is misleading as a significant number of them may be already
immunized at the moment of pregnancy.
The indicator does not reflect other health preventative measures, such as education, diet, and pollution
prevention. The international targets are not very meaningful for many countries.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: The number of infants fully immunized against: DPT;
poliomyelitis; measles; tuberculosis; the number of infants surviving to age one year; the number of
infants living in African countries exposed to yellow fever; the number of pregnant women immunized
against tetanus; and the number of live births.
(b) Data Availability: Data is readily available from national immunization programmes of most
countries, at least at the national level.
(c) Data Sources: Reporting of vaccinations performed annually or nationwide surveys are the most
common data sources.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the World Health Organization (WHO). The contact point is the
Director, Office of Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
(b) Other Organizations: The United Nations Chilren's Fund is a cooperating agency.
7. Further Information
WHO. Global Strategy for Health for All by the Year 2000. Geneva, WHO, 1981.
WHO. Ninth General Programme of Work Covering the Period 1996-2001. Geneva, WHO, 1994.
WHO. World Health Assembly Resolution. WHO45.19, 1992.
WHO. Expanded Programme on Immunization Data Base. Geneva, WHO.
WHO. World Summit for Children. Paris, UNICEF, 1990.
CONTRACEPTIVE PREVALENCE
Social
Chapter 6
Response
1. Indicator
(a)
Name:
Contraceptive
prevalence.
(b) Brief Definition: This indicator is generally defined as the percent of women or reproductive age
using any method of contraception. It is usually calculated for married women of reproductive age, but
sometimes for other base population, such as all women of reproductive age, or for men of a specified
age
group.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
Chapter
(b) Type of Indicator: Response.
6:
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: The measure indicates the extent of people's conscious efforts to control their fertility. It
does not capture all actions taken to control fertility, since induced abortion is common in many
countries.
(b) Relevance to Sustainable/Unsustainable Development: Increased contraceptive prevalence, is,
in general, the single most important proximate determinant of inter-country differences in fertility, and of
ongoing fertility declines in developing countries. Contraceptive prevalence can also be regarded as an
indirect indicator of progress in providing access to reproductive health services including family
planning, one of the eight elements of primary health care.
Agenda 21 discusses reproductive health programmes, which include family planning, as among the
programmes that promote changes in demographic trends and factors towards sustainability. Family
planning is discussed in the broader context of reproductive, sexual health, and reproductive rights by
Chapter VII of the Programme of Action, International Conference on Population and Development
(ICPD); and Strategic Objective C of the Platform for Action adopted at the Fourth World Conference on
Women. Health benefits include the ability to prevent pregnancies that are too early, too closely spaced,
too late, or too many.
Current contraceptive practice depends not only on people's fertility desires, but also on availability and
quality of family planning services; social traditions that affect the acceptability of contraceptive use; and
other factors, such as marriage patterns and traditional birth-spacing practices, that independently
influence the supply of children.
(c) Linkages to Other Indicators: The level of contraceptive use has a strong, direct effect on the total
fertility rate (TFR) and, through the TFR, on the rate of population growth. Use of contraception to
prevent pregnancies that are too early, too closely spaced, too late, or too many has benefits for
maternal and child health. This indicator is also closely linked to access to primary health care services
particularly those pertaining to reproductive health care. Furthermore, it has broader and predictive
implications for many other sustainable development indicators and issues, such as rate of change of
school-age population, woman's participation in the labour force, and natural resource use.
(d) Targets: International agreements do not establish specific national or global targets for
contraceptive prevalence. Recent international conferences have strongly affirmed the right of couples
and individuals to chose the number, spacing and timing of their children, and to have access to the
information and means to do so. The ICPD Programme of Action states that "Governmental goals for
family planning should be defined in terms of unmet needs for information and services. Demographic
goals, while legitimately the subject of government development strategies, should not be imposed on
family-planning providers in the form of targets or quotas for the recruitment of clients" (paragraph 7.12).
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The standard indicator is the percentage currently using
any method of contraception among married women aged 15-49 or 15-44. In this context, the married
group usually includes those in consensual or common-law unions in societies where such unions are
common. Contraceptive prevalence is also frequently reported for all women of reproductive age, and
statistics are sometimes presented for men instead of, or in addition to, women.
Users of contraception are defined as women who are practising, or whose male partners are practising,
any form of contraception. These include female and male sterilization, injectable and oral
contraceptives, intrauterine devices, diaphragms, spermicide, condoms, rhythm, withdrawal and
abstinence, among others.
For this indicator, too early is defined as under age 15. Such adolescents are 5 to 7 times more likely to
die in pregnancy and childbirth than women in the lowest risk group of 20-24 years. Too closely spaced
means women who become pregnant less than two years after a previous birth. Greater adverse
consequences to women and their children are experienced under such circumstances. Women who
have had five or more pregnancies (too many) or who are over 35 (too late), also face a substantially
higher risk than the 20-24 year old group.
When presenting information about contraceptive use, it is useful to show the data according to specific
type of contraception; by social characteristics such as rural/urban or region of residence, education,
marital status; by 5-year age group, including specific attention to adolescents aged under 18 years; and
by family size.
(b) Measurement Methods: Measurements of contraceptive prevalence come almost entirely from
representative sample surveys of women or men of reproductive age. Current use of contraception is
usually assessed through a series of questions about knowledge and use of particular methods.
(c) The Indicator in the DSR Framework: This indicator focuses on individual preventative action to
control fertility through family planning. It is a Response indicator with wide implications for many
elements of the DSR Framework.
(d) Limitations of the Indicator: For surveys, under-reporting can occur when specific methods are not
mentioned by the interviewer. This can be the case with the use of traditional methods such as rhythm
and withdrawal, and use of contraceptive surgical sterilization. The list of specific methods is not
completely uniform in practice, but in most cases is sufficiently consistent to permit meaningful
comparison. "Current" use is often specified in surveys to mean "within the last month", but sometimes
the time reference is left vague, and occasionally longer reference periods are specified. With statistics
from family planning programmes, the accuracy of the assumptions is often difficult to assess. The
derived estimates obviously omit contraceptive users who do not use the programme's services, and
thus tend to underestimate the overall level of use.
Service statistics maintained by family planning programmes are also sometimes used to derive
estimates of contraceptive prevalence. In such cases it is necessary to apply assumptions in order to
derive estimates of numbers of current users from the records of numbers of family planning clients.
Base population statistics (numbers of women or of married women) are in this case usually derived
from census counts, adjusted to the reference date by the Population Division of the Department of
Economics and Social Information and Policy Analysis (DESIPA), as part of its preparations of the
official United Nations population estimates and projections.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Number of women of childbearing age using family
planning methods. Number of women of childbearing age. Both data sets are frequently limited to
married women.
(b) Data Availability: The most recent United Nations review of contraceptive prevalence includes
statistics for 119 countries and areas with information dating from 1975 or later. These countries include
90 per cent of world population. This review includes contraceptive prevalence measures for all women
of reproductive age in 64 countries and areas and for samples of men in 27 countries and areas.
Contraceptive prevalence is one of the few topics for which data coverage is more complete and more
current for developing than for developed countries. Most surveys provide estimates for major regions
within countries as well as at the national level. Less frequently the sample design permits examining
prevalence at the state, provincial, or lower administrative levels. In addition to those with national or
near-national coverage, surveys covering this topic are sometimes available for particular geographic
areas. Data are much less widely available for population groups other than married women, although
such information has increased in recent years.
(c) Data Sources: Executing agencies for surveys covering this topic vary. National statistical offices
and ministries of health are the most common source, but other governmental offices, non-governmental
voluntary or commercial organizations are frequently involved. Many surveys are conducted in
collaboration with international survey programmes. The Population Division, DESIPA regularly
compiles information about contraceptive prevalence and publishes it in the annual World Population
Monitoring report.
6. Agencies Involved in the Development of the Indicator
The lead agencies are: the United Nations Department of Economics and Social Information and Policy
Analysis (DESIPA), with the contact point as the Director, Population Division, fax no. (1 212) 963 2147;
and the World Health Organization (WHO), with the contact point as the Director, Office of Global and
Integrated Environmental Health, fax no. (41 22) 791 4123.
7. Further Information
Levels and Trends of Contraceptive Use as Assessed in 1988 (United Nations, Sales No. E.89.XIII.4).
Levels and Trends of Contraceptive Use as Assessed in 1994 (United Nations, ST/ESA/SER.A/146,
forthcoming).
Programme of Action of the International Conference on Population and Development, Report of the
International Conference on Population and Development, Cairo, Egypt, September 5-13, 1994. (United
Nations Document - A/CONF. 171/13).
World Population Monitoring, 1993 (Sales No. E.95.XIII.8, New York).
World Population Monitoring, 1996 (ESA/P/WP.131).
PROPORTION OF POTENTIALLY HAZARDOUS CHEMICALS MONITORED IN FOOD
Social
Chapter 6
Response
1. Indicator
(a)
Name:
Proportion
of
potentially
hazardous
chemicals
monitored
in
food.
(b) Brief Definition: Proportion of potentially hazardous chemicals monitored in food which are
appropriate
for
the
country's
stage
of
development.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
Chapter
(b) Type of Indicator: Response.
6:
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: The purpose of this indicator is to assess national capacities to monitor, through
population-based sampling and analysis, the presence of potentially hazardous chemicals in various
food commodities, based on lists of priority chemicals and foods in which they occur, appropriate for the
country's stage of development.
(b) Relevance to Sustainable/Unsustainable Development: Human health care is integral to the
achievement of the goals of sustainable development. Food contamination is a major route of human
exposure to a range of chemicals potentially hazardous to health. Food contamination monitoring is
essential to protect public health and maintain confidence in the food supply. Taken together with
information on food consumption, monitoring provides an assessment of whether human exposure to
chemicals in food exceeds established acceptable or tolerable levels. In this way, monitoring provides
information to identify problems, establish priorities, and select appropriate interventions. Monitoring can
also detect sporadic contamination which is often associated with chemical misuse or accidents. Food
contamination monitoring serves to confirm the adequacy of source directed (environmental) measures
and other interventions to reduce or prevent the contamination of food.
(c) Linkages to Other Indicators: This indicator is closely linked with other measures associated with
human exposure to chemicals, such as use of agricultural pesticides, ambient air pollution, unintentional
chemically induced acute poisonings, and generation of hazardous waste. It is also linked to other
health response indicators, such as total national health care expenditure related to Gross National
Product (GNP).
(d) Targets: It is generally accepted that at least 90% of the contaminant/food commodity combinations
should be monitored.
(e) International Conventions and Agreements: The Food Contamination Monitoring and
Assessment Programme (GEMS/Food) of the Global Environment Monitoring System is of relevance to
this indicator.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The definitions and concepts for this indicator are well know
and readily available. Monitoring is the representative (random) sampling and analysis of selected food
commodities, including drinking water, to assess the dietary exposure of the population to a potentially
hazardous contaminant for comparison with the acceptable or tolerable levels of human exposure
established by national and international bodies. Such monitoring should not be confused with
compliance monitoring which is performed for regulatory purposes.
(b) Measurement Methods: This indicator may be calculated by using: the number of combinations of
contaminants and foods which are monitored as the numerator; and the number of combinations of
contaminants and foods which should be monitored by the country at its stage of development as the
denominator.
Based on over twenty years of GEMS/Food experience, three separate standard lists of
contaminant/food combinations have been prepared based on knowledge of potentially hazardous
chemicals and the foods in which they are known to occur. The core list for lesser developed countries
contains 153 combinations of contaminants and foods which offer basic protection of the consumer from
known chemical hazards. The intermediate list for developing countries contains 358 combinations of
contaminants and foods which offer improved protection of the consumer, especially as development
increases the number and amount of potentially hazardous chemicals used in the country. The
comprehensive list for industrialized countries includes 394 combinations which provide assurance that
the full range of potentially toxic chemicals are being monitored in the food supply. For guidance on
which list to select, countries with per capita GNP under US$3 500 should use the core list. For counties
with per capita GNP between US$3 500 and US$7 500, the intermediate list should be used. For
countries with per capita GNP over US$7 500, the comprehensive list should be used. The lists are
attached in Annex 1 below.
(c) The Indicator in the DSR Framework: This indicator represents a societal Response to human
exposure to potentially hazardous chemicals.
(d) Limitations of the Indicator: Frequency of monitoring, which is based on the importance of the food
in the diet and to total exposure, is not addressed by this indicator.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: The number of contaminant/commodity combinations
monitored are required (see section 4b above).
(b) Data Availability: The information is available for most countries through the ministries of health,
agriculture, and/or environment.
(c) Data Sources: The information may be obtained directly from the laboratories with the mandate to
collect it. Most countries undertaking monitoring usually publish annual reports, often in professional
journals. In over seventy countries, the GEMS/Food Programme maintains a network of Participating
Institutions which are involved in this type of monitoring.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the World Health organization (WHO). The contact point is the
Director, Office of Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
(b) Other Organizations: The Food and Agriculure Organization (FAO) and the United Nations
Environment Programme (UNEP) are partners with WHO in the GEMS/Food Programme.
7. Further Information
World Health Organization. Guidelines for Establishing or Strengthening National Food Contamination
Monitoring Programmes. Unpublished Document WHO/HCS/FCM/78.1. GEMS/Food, Geneva.
World Health Organization. Guidelines for Predicting Dietary Intake of Pesticide Residues. GEMS/Food,
Geneva. 1990.
World Health Organization. Guidelines for the Study of Dietary Intake of Chemical Contaminants. WHO
Offset Publication No 87. GEMS/Food, Geneva. 1985.
ANNEX 1
CORE LIST
Contaminant
Food
aldrin, dieldrin, DDT (p,p'- and o,p'-), TDE (p,p'-), TDE
(p,p'-), DDE (p,p'-) endosulfan ( and ß), endosulfan
whole milk, butter, animal fats and oils, fish,
cereals*, human milk
sulfate,
endrin,
hexachlorocyclohexane
( and ß and ), hexachlorobenzene, heptachlor,
heptachlor epoxide and polychlorinated biphenyls
lead
milk, canned/fresh meat, kidney, cereals*,
canned/fresh fruit, fruit juice, spices, infant
food, canned beverages, wine, drinking
water
cadmium
kidney, molluscs, crustaceans, cereals*
mercury
fish
aflatoxins
milk, maize, groundnuts, other nuts, dried
figs
diazinon, fenitrothion, malathion, parathion, methyl
parathion, methyl pirimiphos
cereals*, vegetables, drinking water
* Or other staple foods
INTERMEDIATE LIST
Contaminant
Food
aldrin, dieldrin, DDT (p,p'- and o,p'-), TDE (p,p'-),
TDE (p,p'-), DDE (p,p'-) endosulfan ( and ß),
endosulfan sulfate, endrin, hexachlorocyclohexane
( and ß and ), hexachlorobenzene, heptachlor,
heptachlor epoxide and polychlorinated biphenyls
(congeners No. 28, 52, 101, 118, 138, 153 and
180)
whole milk, dried milk, butter, eggs, animal fats
and oils, fish, cereals*, vegetable fats and oils,
human milk, total diet, drinking water
lead
milk, canned/fresh meat, kidney, fish, molluscs,
crustaceans,
cereals*,
pulses,
legumes,
canned/fresh fruit, fruit juice, spices, infant food,
canned beverages, wine, total diet, drinking water
cadmium
kidney, molluscs, crustaceans, cereals* flour,
vegetables, total diet
mercury
fish, fish products, total diet
aflatoxins
milk, milk products, maize, cereals*, groundnuts,
other nuts, spices, dried figs, total diet
diazinon, fenitrothion, malathion, parathion, methyl
parathion, methyl pirimiphos, chlorpyrifos
cereals*, vegetables, fruit, total diet, drinking water
radionuclides (Cs-137, Sr-90, I-131, Pu-239)
cereals*, vegetables, milk, drinking water
nitrate/nitrite
vegetables, drink water
* Or other staple foods
COMPREHENSIVE LIST
Contaminant
Food
aldrin, dieldrin, DDT (p,p'- and o,p'-), TDE (p,p'-), TDE (p,p'-), DDE
(p,p'-) endosulfan ( and ß), endosulfan sulfate, endrin,
hexachlorocyclohexane ( and ß and ), hexachlorobenzene,
whole milk, dried milk, butter,
eggs, animal fats and oils, fish,
cereals*, vegetable fats and oils,
heptachlor, heptachlor epoxide and polychlorinated biphenyls
(congeners No. 28, 52, 101, 118, 138, 153 and 180), dioxins
(PCDDs and PCDFs)
human milk, total diet, drinking
water
lead
milk, canned/fresh meat, kidney,
fish,
molluscs,
crustaceans,
cereals*,
pulses,
legumes,
canned/fresh fruit, fruit juice,
spices, infant food, total diet,
drinking water
cadmium
kidney, molluscs, crustaceans,
cereals*, vegetables, total diet
mercury
fish, fish products, mushrooms,
total diet
aflatoxins
milk, milk products, eggs, maize,
cereals*, groundnuts, other nuts,
spices, dried figs, total diet
ochratoxin A
wheat, cereals, meat (pork)
patulin
apples, apple juice, other pome
fruit and juice
fumonisins
maize
diazinon, fenitrothion, malathion, parathion, methyl parathion,
methyl pirimiphos, chlorpyrifos
cereals*, vegetables, fruit, total
diet, drinking water
dithiocarbamates
cereals*, vegetables, fruit, total
diet, drinking water
radionuclides (Cs-137, Sr-90, I-131, Pu-239)
cereals*, vegetables, milk, drink
water
nitrate/nitrite
vegetables, drinking water
* Or other staple foods
NATIONAL HEALTH EXPENDITURE DEVOTED TO LOCAL HEALTH CARE
Social
Chapter 6
Response
1. Indicator
(a)
Name:
National
health
expenditure
devoted
to
local
health
care.
(b) Brief Definition: Proportion of national health expenditure devoted to local primary health care. This
is the first-level contact and includes community health care, health centre care, dispensary care, etc.,
but
excludes
hospital
care.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter 6: Protecting and Promoting Human Health.
(b) Type of Indicator: Response.
3. Significance (Policy Relevance)
(a) Purpose: This indicator measures the proportion of resources devoted to primary health care.
(b) Relevance to Sustainable/Unsustainable Development: Everybody now agrees that significant
health progress worldwide can only be achieved through universal access to primary health care, that is
essential health care made accessible to all at an affordable cost. The proportion of the national health
expenditure devoted to local health care is an indicator of the effort made by a society to finance
essential and easily accessible health care.
(c) Linkages to Other Indicators: This indicator is closely linked to other health care indicators, such
as total national healthcare as a percent of Gross National Product, immunization against infectious
childhood diseases, and infant and maternal mortality rates.
(d) Targets: Not available.
(e) International Conventions and Agreements: Not available.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Local Health Care: first-level contact, including community
health care, health centre care, dispensary care and the like, excluding hospital care. National health
expenditure includes: Public: current and capital expenditure of ministries of health and other ministries
with responsibilities in the health sector, and social security expenditure, including external aid for the
health sector; Private: out-of-pocket health expenditure, patient co-payments, private health insurance
premiums, and health expenditures by non-government organizations (NGOs).
(b) Measurement Methods: Numerator: national health expenditure on local health care; Denominator:
total national health expenditure.
(c) The Indicator in the DSR Framework: In reflecting the proportion of total health care expenditures
devoted to local health care, this is a Response indicator in the DSR Framework.
(d) Limitations of the Indicator: The definition does not take into account primary health care activities
which are delivered in hospitals, nor the cost of central and regional activities needed to support and
guide local health care. Furthermore, each country will have to define what is "local health care" with
respect to its own health system.
The indicator says nothing about the quality or efficiency of health actions and services. Household
surveys are required to generate the information needed for this indicator which may pose a significant
burden for some countries.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: A large amount of financial data are needed from a wide
variety of sources, as can be seen from the definition.
(b) Data Availability: Data on out-of-pocket health expenditures requires a household survey. All other
data should usually be available from responsible institutions at the national level (public or private).
(c) Data Sources: The primary sources of data are national ministries of health, finance, and regional
development; and NGOs.
6. Agencies Involved in the Development of the Indicator
The lead agency is the World Health Organization (WHO). The contact point is the Director, Office of
Global and Integrated Environmental Health, WHO; fax no. (41 22) 791 4123.
7. Further Information
WHO. Development of Indicators for Monitoring Progress Towards Health for All by the Year 2000.
Geneva, 1981.
WHO. Global Strategy for Health for All by the Year 2000. Geneva, 1981.
TOTAL NATIONAL HEALTH EXPENDITURE RELATED TO GROSS NATIONAL PRODUCT
Social
Chapter 6
Response
1. Indicator
(a) Name: Total national health expenditure related to gross national product (GNP).
(b) Brief Definition: This indicator is defined as the share of GNP devoted to health expenditure. It
includes
public
and
private
expenditure.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a)
Agenda
21:
Chapter
(b) Type of Indicator: Response.
6:
Protecting
and
Promoting
Human
Health.
3. Significance (Policy Relevance)
(a) Purpose: The purpose of the indicator is to measure the proportion of national resources devoted to
health.
(b) Relevance to Sustainable/Unsustainable Development: Health and sustainable development are
intimately interconnected. This measure provides a first indication of the priorities granted to health as
compared to other sectors within the same country. It allows comparisons of the priority given to health
between countries.
(c) Linkages to Other Indicators: Health expenditures is closely linked to other indicators measuring
the fiscal support for the provision of basic needs, such as GDP spent on education.
(d) Targets: The Global Strategy for Health for All by the Year 2000 states that at least 5% of the Gross
National Product should be spent on health (see section 7 below).
(e) International Conventions and Agreements: See section 3d above.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The definitions for national health expenditure are well
established and include:
i) Public: The current and capital expenditure of the Ministry of Health and other ministries with
responsibilities in the health sector; and social security expenditure. It also includes external aid for the
health sector.
ii) Private: This definition covers out-of-pocket health expenditure, patient co-payments, private health
insurance premiums, and health expenditures by non-government organisations.
iii) Gross National Product: GNP consists of the Gross Domestic Product (the total output of goods and
services for final use produced by residents) plus net factor income from abroad. This second aspect is
the income citizens receive from abroad for factor services, less similar payments made to foreigners
who contribute to the domestic economy.
(b) Measurement Methods: The numerator is the sum of public and private expenditures on health,
while the denominator is the GNP, both measured on a national basis.
(c) The Indicator in the DSR Framework: This indicator deals with the share of GNP devoted to
national health. It provides a summary Response indicator within the DSR Framework.
(d) Limitations of the Indicator: The cost of health care, the efficiency of the health care systems, and
the quality of the services provided affect the level of health expenditure. It is sometimes difficult to
identify all elements of public and private health expenditure, for example military and traditional
expenditures. The assessment of out-of-pocket expenditure requires a household survey which may
prove to be a burden for some countries. Difficulties could arise with respect to estimating private health
expenditure. If estimated via extrapolation of data from small-scale household surveys, mention should
be made of the survey scope.
(e) Alternative Definitions: Not available.
5. Assessment of the Availability of Data from International and National Sources
(a) Data Needed to Compile the Indicator: Public current and capital health expenditure (including
external aid), together with private health expenditure and GNP.
(b) Data Availability: Most are normally available from the ministries of health, finance and/or planning,
and any other ministry engaged in health expenditures. Data may not be readily available for private
health expenditure.
(c) Data Sources: Primary sources of data are the budget of the ministry of health and the national
budget.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the World Health Organisation (WHO), with the contact point as
the Director, Office of Global and Integrated Environmental Health, WHO; fax no. (41 22 791 4123).
(b) Other Organizations: The World Bank and the Organisation for Economic Co-operation and
Development contributed to the development of this indicator.
7. Further Information
WHO. Global Strategy for Health for all by the Year 2000. Geneva, WHO, 1981.
Chapter 7: Promoting sustainable human settlement development








Rate of growth of urban population
Per capita consumption of fossil fuel by motor vehicle transport
Human and economic loss due to natural disasters
Percent of population in urban areas
Area and population of urban formal and informal settlements
Floor area per person
House price to income ratio
Infrastructure expenditure per capita
Chapter 7: Promoting
development
sustainable
human
RATE OF GROWTH OF URBAN POPULATION
Social
Chapter 7
Driving Force
settlement
1. Indicator
(a)
Name:
Rate
of
growth
of
urban
population.
(b) Brief Definition: The average annual rate of change of population living in defined urban areas
during
a
specified
period.
(c) Unit of Measurement: Usually expressed as a percentage.
2. Placement in the Framework
(a) Agenda 21: Chapter 7: Promoting
(b) Type of Indicator: Driving Force.
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: This indicator measures how fast the size of urban population is changing. It aggregates
impacts of natural increase in urban population, net rural-to-urban migration, and increased land area
with urban characteristics.
(b) Relevance to Sustainable/Unsustainable Development: Urban areas promise economic
efficiency and potential for development deriving from concentration of population, business and
industries. However, when needs of a rapidly growing population in urban areas go beyond
governments' ability to meet them, sustainability of urban development can be threatened. Needs of a
growing population range from food, housing, land, employment, and education to environmental
infrastructure including water supply, sanitation, and waste collection services. Demands for more and
better urban services present one of the major challenges for local and national governments. The
usefulness of this indicator is increased if growth rates are available for selected urban size categories.
(c) Linkages to Other Indicators: This indicator has close linkages with other socioeconomic variables,
including percentage of population in urban areas, growth in school age population, and overall
population growth. It is also linked to many environmental indicators, such as land use change, water
withdrawals, and generation of municipal waste.
(d) Targets: International agreements have not established specific national or global targets for this
indicator.
(e) International Conventions and Agreements: Not applicable, see section 3d above.
4. Methodological Description and Underlying Definitions
The urban growth rate for a country is generally based on an intercensal urban growth rate calculated
from two censuses, each adjusted for incompleteness. The demarcation of urban areas is usually
defined by countries as part of census procedures, and is usually based on the size of localities,
classification of areas as administrative centres, or classification of areas according to special criteria
such as population density or type of economic activity of residents. Data on urban population are
characterized by the same limitations as total population, for example, under-enumeration of population
in censuses (which may differ between urban and rural areas).
There is no internationally agreed definition of urban areas, and national definitions vary from country to
country. Consistency in the breakdown of what constitutes urban and rural areas is problematic. With
growth, the boundaries of urban areas change over time.
The Population Division of the United Nations Department of Economics and Social Information and
Policy Analysis (DESIPA) evaluates, and adjusts whenever necessary, urban and rural data for underenumeration and inconsistencies, as part of its biennial revision of the United Nations urban and rural
population estimates and projections.
5. Assessment of the Availability of Data from National and International Sources
As indicated above, the rate of growth of urban population for a country is generally calculated from data
on urban population from two censuses. The Statistical Division, DESIPA recommends that countries
take censuses every 10 years, and these data can be used to calculate an intercensal population growth
rate. In recent decades most countries have carried out censuses: 204 countries or areas carried out a
census during the 1990 census decade (1985 to 1994). Data is also available from special country
questionnaires sent to national statistical offices from the Statistical Division, DESIPA. Such census data
also provide the basis for examining urban growth rates for sub-national areas. For all countries, urban
data are evaluated and, if necessary, adjusted for incompleteness by the Population Division, DESIPA
as part of its preparation of the official United Nations urban and rural population estimates and
projections. Past, current and projected urban growth rates are prepared for all countries by the
Population Division, DESIPA and appear in the United Nations publication, World Urbanization
Prospects: The 1994 Revision (see section 7 below).
6. Agencies Involved in the Development of the Indicator
The lead organization is United Nations Department for Economic and Social Information and Policy
Analysis (DESIPA). The contact point is the Director, Population Division, DESIPA; fax no. (1 212) 963
2147.
7. Further Information
DESIPA. World Urbanization Prospects: The 1994 Revision. Population Division. United Nations
publication, Sales No. E.95.XIII.12. New York, 1995.
DESIPA. 1993 Demographic Yearbook. Statistical Division. United Nations publication, Sales No.
E/F.95.XIII.1. 1995.
PER CAPITA CONSUMPTION OF FOSSIL FUEL BY MOTOR VEHICLE TRANSPORT
Social
Chapter 7
Driving Force
1. Indicator
(a) Name: Per capita consumption of fossil fuel by motor vehicle transport.
(b) Brief Definition: Defined as the annual number of litres per person of fossil fuel consumed by motor
vehicle
transport
in
urban
areas.
(c) Measurement Unit: Litres.
2. Placement in the Framework
(a) Agenda 21: Chapter: 7: Promoting
(b) Type of Indicator: Driving Force.
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: This indicator measures surface transport consumption of fossil fuels within urban areas.
(b) Relevance to Sustainable/Unsustainable Development: Reduced consumption of non-renewable
fossil fuels, and, indirectly, reduced use of motor vehicles, is a prerequisite for sustainable human
settlements development, since it affects the whole ecosystem on a substantial scale. This indicator is
particularly relevant to decision making for urban areas.
As motor vehicles are the main users of transport fuel, the indicator is highly correlated with motor
vehicle usage, which in turn measures indirectly the pressure on the environment through use of
resources, energy consumption, air pollutant emission (particularly ozone, particulate matter, carbon
monoxide and nitrogen oxide), noise pollution. The indicator also provides indirect information about
urban congestion and contamination of land and water. Fuel consumption is highly dependent on urban
land use pattern, particularly density, and the fuel efficiency of the vehicle fleet. Increasing fuel
consumption may be the consequence of suburbanization of the work force, increasing income and car
ownership, and reduction of passenger numbers per vehicle. Fuel consumption is a good indicator of
automobile dependence and, for certain countries, of import oil dependence.
(c) Linkages to Other Indicators: This indicator has many linkages to other socioeconomic and
environmental indicators, especially those related to consumption, human settlements, and protection of
the atmosphere. There are direct links, for example, to the emission of sulphur oxides (SOx) and
nitrogen oxides (NOx), reductions in the emissions of greenhouse gases, energy use, and land use
change. In consequence, there are implications for ambient concentration of pollutants in urban areas,
human health, ozone depletion, and expenditure on air pollution abatement.
(d) Targets: No international targets have been established. Some countries have fuel consumption
targets for the automobile vehicle fleet.
(e) International Conventions and Agreements: Not applicable, see section 3d above.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Transport fuel should include fossil fuel such as petrol
(gasoline), diesel, liquefied petroleum gas, gasohol, but should exclude aviation fuel.
(b) Measurement Methods: Fuel consumption is always available at the national level, but it is more
difficult to calculate for the city, as much fuel purchased in the city may be used for intercity hauling.
Fuel purchased within the city forms part of the city product, so one approach is to count all fuel
purchased within the city. On the other hand, if the emphasis is on resource usage within the city, then
only intra urban trips should be counted, and it may be preferable to multiply the size of the vehicle fleet
of personal and commercial vehicles by estimated average fuel consumption.
(c) The Indicator in the DSR Framework: Transport fuel consumption, as an indicator of automobile
dependence (and oil dependence in some countries), measures the consumption of non-renewable
resources and the negative pressure and impact of motor vehicle transport on the environment in
human settlements. As such, it is a Driving Force indicator within the DSR Framework. It is interlinked
with many State and Response indicators (see section 3c above).
(d) Limitations of the Indicator: It is conceptually difficult to separate motor vehicle fuel use for urban
areas from non-urban areas (see section 4b above). Data for the indicator are not as readily available as
for countries as a whole. While the indicator captures most fossil fuel use by motor vehicles, it does not
reflect fuel used to generate electricity for transport, neither does it include fuel used for other surface
forms, such as rail. Fuel consumption may have various impacts on the environment depending on fuel
type, vehicle emissions, urban density, traffic and the road pattern. These factors should be considered
in the interpretation of the indicator.
(e) Alternative Definitions: In recognition of the difficulties of measuring and defining the scope of the
impact of this indicator, it is suggested that per capita consumption of fossil fuel on a national basis
represents an alternative indicator. Such an indicator has a broader relevance for consumption pattern,
but does not focus on human settlement sustainability.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Consumption of petrol (gasoline), diesel, liquefied
petroleum gas, and gasohol, used for transport purposes. Urban population.
(b) Data Availability: Fuel consumption is always available at the national level, usually from the
ministry responsible for transportation, but it is more difficult to calculate for urban areas (see section 4b
above). Data for this indicator are collected by the United Nations Centre for Human Settlements
(UNCHS or Habitat) at the city level, as an extensive indicator. They are collected by the following
international organizations at the national level: The Statistical Division, the United Nations Department
of Economics and Social Information and Policy Analysis (DESIPA) publishes this indicator in its Energy
Statistics Yearbook. The International Roads Federation collects and publishes appropriate data, except
for alternative fuels such as gasohol, in its World Road Statistics biennial compendium. The
Organisation for Economic Co-operation and Development (OECD) publishes a biennial Environmental
Data Compendium which includes total final energy consumption by transport sector by mode.
(c) Data Sources: See section 5b above.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the United Nations Centre for Human Settlements (Habitat). The
contact point is the Director, Programme Coordination, Habitat; fax no. (254 2) 624 266.
(b) Other Organizations: The International Road Federation and the Statistical Division of DESIPA
have assisted with the development of this indicator.
7. Further Information
OECD. Transport and the Environment. OECD, Paris, 1988.
OECD. OECD Environmental Data: Compendium 1995. OECD, Paris, 1995.
Newman, Peter W.G. and Jeffrey R.K. Kenworthy. Cities and Automobile Dependence: a Sourcebook.
Gower, England, 1991.
UNCHS (Habitat). Monitoring the City. Urban Indicators Review. UNCHS, Nairobi, 1995.
DESIPA. Energy Statistics Yearbooks.
International Roads Federation. World Road Statistics.
HUMAN AND ECONOMIC LOSS DUE TO NATURAL DISASTERS
Social
Chapter 7
Driving Force
1. Indicator
(a)
Name:
Human
and
economic
loss
due
to
natural
disasters.
(b) Brief Definition: The number of persons dead and missing as a direct result of a natural disaster;
and the amount of economic and infrastructure losses incurred as a direct result of the natural disaster.
(c) Measurement Unit: Number of bodies or persons; $US.
2. Placement in the Framework
(a) Agenda 21: Chapter 7: Promoting
(b) Type of Indicator: Driving Force.
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: To provide estimates of the human impact and the economic impact of disasters and
emergencies over time and across administrative units in order to measure the trends in population
vulnerability. The indicators can be used by decision makers at all levels to determine whether their
country or province is getting progressively more or less prone to the effects of disasters.
(b) Relevance to Sustainable/Unsustainable Development: Natural disasters cause loss of life,
disruption of economic activities and urban productivity, particularly for highly susceptible low-income
groups; and environmental damage, such as loss of fertile agricultural land, and water contamination. It
can result in major re-settlement of populations.
While the number of disaster events may not be increasing, the growing vulnerability of populations
(population pressures on land, increasing urbanisation and risky land-use, marginalisation of
populations, civil unrest, etc.) imply that the impacts are becoming greater. At the same time, decreasing
national and donor budgets reflect the need for better planning, preparedness, and coordination.
The value of this indicator is a function of the different factors that define the risk of death and damage,
that is the frequency of events, the size of the population and capital in the affected area, and the
capacity of the local population and government to prevent disasters or to respond. This indicator lends
itself for use in an assessment that takes into account the changes in each of these components.
(c) Linkages to Other Indicators: The immediate and longer term implications of this indicator are
linked to a number of other socioeconomic, environmental, and institutional measures, such as
population density, access to safe drinking water, population in informal and formal urban areas,
development assistance, land use, and access to information.
(d) Targets: Not available.
(e) International Conventions or Agreements: The General Assembly of the United Nations has
proclaimed the 1990s as the International Decade for Natural Disaster Reduction.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The definitions and concepts for this indicator are not well
established with common acceptance. However, for the purpose of this indicator, the following definition
of natural disaster used by the Global Disaster Database is suggested: a disaster is a situation or event
which overwhelms local capacity, necessitating a request to the national or international level for
external assistance, or is recognised as such by a multilateral agency or by at least two sources, such
as national, regional, or international assistance groups and the media.
All disasters can be identified by several common elements, such as affected country, human and
economic impact, etc. Catastrophic phenomena that affect more than one country are regarded as a
combination of specific disasters occurring in each affected country and are therefore to be recorded
separately for each affected country. For a long-term disaster spanning over a duration of time, some of
the relevant data (for example, contributions, affected population) will have to be recorded per year
while other characteristics (for example., disaster type, damage) are unique to the disaster and can be
stored in one record. In the case of concurrent disasters in the same country or area, events or
situations can be linked together, if there is a causal relationship, or identified separately if they require
appeals for assistance. For example, cyclonic storms that generate floods can be considered as being
part of the same emergency situation, while epidemics occurring several months after a volcanic
eruption have to be considered as separate events.
(b) Measurement Methods: The measurement methods proposed are based on the criteria used by the
Centre for Research on the Epidemiology of Disaster (CRED). The data elements included here have
been selected and modified according to the requirements of the sustainable development indicator
methodology sheets. Overall, these data should be collected and validated at the country level by a
public authority using these standard criteria and methods. Each element is presented first in a concise
description, followed by comments and the proposed recording procedure.
i) Onset Date: This establishes the date when the disaster situation occurred. This date is well defined
for all sudden-impact disasters. For disaster situations which develop gradually overtime (for example,
drought) scientific (meteorology and seismology institutes) and governmental (civil defence authorities)
sources.
ii) Declaration Date: The date when the first call for external assistance concerning the disaster is
issued. This call for external assistance mentioned here is defined according to the definition of a
disaster situation stated above. This date is available for all disaster situations to be included for the
indicator. Only the date of the first appeal for external assistance is recorded.
iii) Disaster Type: This describes the disaster according to a pre-defined classification scheme. Disaster
types should include all types of natural disasters, for example, earthquakes, cyclones, floods, volcanic
eruptions, drought, and storms. Disasters may be further described as sudden onset, such as
earthquakes and floods, and long-term, such as drought. Two or more disasters may be related, or other
disaster types may occur as a consequence of a primary event. For example, a cyclone may generate a
flood or landslide; or an earthquake may cause a gas line to rupture.
iv) Country: This defines the country in which the disaster occurred. Every disaster record will be by
country. Autonomous regions, not yet recognised as countries, will not be used. The same disaster may
affect more than one country, and here separate records are maintained.
v) Dead: This includes persons confirmed dead and persons missing and presumed dead. Official
figures are used whenever available. The figure is updated as missing persons are confirmed to be
dead.
vi) Estimated Amount of Damage: This represents the value of all damages and economic losses
directly related to the occurrence of the given disaster. The economic impact of a disaster usually
consists of direct (for example, damage to infrastructure, crops, housing) and indirect (for example, loss
of revenues, unemployment, market destabilisation) consequences on the local economy. Although
several institutions have developed methodologies to quantify these losses in their specific domain, no
standard procedure to determine a global figure for the economic impact exists. Three different figures
are recorded from sources which have a well-defined methodology for the assessment of economic
impacts, including the World Bank and other international lending agencies; the host government; and,
especially in the case of complex emergency situations, the total budget requirements listed in the
consolidated appeals launched by UN agencies and other major non-government organizations.
(c) The Indicator in the DSR Framework: Natural disasters can have devastating short and long term
impacts on local and national life adversely affecting progress towards sustainable development. They
represent a Driving Force indicator in the DSR Framework.
(d) Limitations of the Indicator: The validity of these indicators are limited to the quality and the
standardised reporting of the data used for its calculation. Use of data from insurance firms for example
will introduce serious bias in the data and therefore in its interpretation. Comparability over time
represents a particular problem for this indicator.
(e) Alternative Definitions: If the indicator has to reflect changing risk, the measurement should be
loses per unit of time per capita. This is not possible without further development of the indicator
methodology.
5. Assessment of the Availability of Data from National and International Sources
Internationally, the data are maintained by the Centre for Research on the Epidemiology of Disasters
(CRED) in Brussels. The Centre serves as a reference source for most applications. CRED compiles
and validates data from diverse sources, including the Office of Foreign Disaster Assistance (USAID),
United Nations Department of Humanitarian Affairs (UNDHA), Munich Re, Suisse Re, Lloyds of
England, and Royale Belge, the World Bank, World Health Organization, United Nations Development
Programme (UNDP), the International Federation of the Red Cross and Red Crescent Societies, the
International Committee of the Red Cross. National agencies and vary from country to country, but
generally includes civil defence organizations, ministries of interior and agriculture, etc.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the United Nations Department of Humanitarian Affairs (UNDHA).
The contact point is the Director, Secretariat for the International Decade for Natural Disaster Reduction
(IDNDR); fax no. (41 22) 733 8695.
(b) Other Organisations: Other contributing organizations include the Centre for Research on the
Epidemiology of Disasters, Faculty of Medicine, University of Louvain, Brussels. The following
organizations were consulted over the development of this indicator methodology sheet: World Food
Programme, United Nations Environment Programme, Pan American Health Organization, International
Federation of the Red Cross and Red Crescent Societies, and US Agency for International
Development.
7. Further information
CRED. Profiles in the World: Summary of Disaster Statistics by Continent. CRED Statistical Bulletin,
May 1994.
International Federation of Red Cross and Red Crescent Societies, Centre for Research on the
Epidemiology of Disasters. World Disasters Reports for 1993, 1994, and 1995. Martinus Neijhoof
Publishers, Dordrecht, Netherlands. 1993, 1994, and 1995.
Sapir, D.G. Natural and Man-made Disasters: the Vulnerability of Women-headed Households and
Children without Families. World Health Statistical Quarterly; 46: 227-233, 1993.
CRED. Proposed Principles and Guidelines for the Collection and Dissemination of Disaster Related
Data. Report on the IERRIS Workshop, 7-9 September 1992.
Sapir, D.G. & Sato, T. The Human Impact of Floods: Common Issues for Preparedness and Prevention
in Selected Asia-Pacific Countries. Paper presented at the Second Asian Pacific Conference on
Disaster Medicine, Chiba, Japan. 1992.
Sapir, D.G. and Misson, C. The Development of a Database on Disasters. Disasters; 16(1): 80-86.
1992.
CRED. Statistical Update from CRED Disaster Events Database in: CRED Disasters in the World.
November 1991.
PERCENT OF POPULATION IN URBAN AREAS
Social
Chapter 7
State
1. Indicator
(a)
Name:
Percent
of
population
in
urban
areas.
(b) Brief Definition: The percentage of total population of a country or area living in places defined as
urban.
(c) Unit of Measurement: %.
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State.
7:
Promoting
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: This indicator is the most commonly used index of the degree of urbanization. Although
national definitions of "urban" vary (see section 4 below), there is sufficient uniformity to permit
meaningful comparisons between countries and over time. It is often useful to further classify urban
areas by size, since the benefits and problems of cities vary, in part, with their size.
(b) Relevance to Sustainable/Unsustainable Development: Agenda 21 calls for a balance between
urban and rural development patterns. In addition, urbanization is recognized as an intrinsic dimension
of economic and social development by the Programme of Action of the International Conference on
Population and Development (ICPD). Urban areas have distinctive characteristics reflecting the social
fabric and density of their population, and the nature and scale of economic activities. Urbanization has
profound social and economic implications that extend beyond the urban boundaries. Although many
urban areas have environmental and developmental problems such as housing shortages, traffic
congestion, air and water pollution, and waste, Agenda 21 also notes urban societies' potential for
sustainable development if properly managed.
(c) Linkages to Other Indicators: This indicator has close linkages with other demographic indicators,
particularly the rate of growth of urban population. Since it does not reflect differences in city size, the
indicator of the number of mega-cities adds useful information. Urbanization is also linked to economic
indicators such as manufacturing value added in GDP. Some of the environmental indicators of solid
waste, sewage and pollution are of particular relevance to urban settings.
(d) Targets: International agreements have not established specific national or global targets for this
indicator.
(e) International Conventions and Agreements: Not applicable (see section 3d above).
4. Methodological Description and Underlying Definitions
By definition, this indicator is calculated as the population of urban areas divided by total population of a
country or area, expressed as a percentage. The demarcation of urban areas is usually defined by
countries as part of census procedures, and is usually based on the size of localities, classification of
areas as administrative centres, or classification of areas according to special criteria such as population
density or type of economic activity of residents. Data on urban population are characterized by the
same limitations as total population, for example, under-enumeration of population in censuses (which
may differ between urban and rural areas). The Population Division of the United Nations Department of
Economics and Social Information and Policy Analysis (DESIPA) evaluates, and adjusts whenever
necessary, urban and rural data for under-enumeration and inconsistencies, as part of its biennial
revision of the United Nations urban and rural population estimates and projections.
There is no international agreed definition of urban areas, and national definitions vary from country to
country. Consistency in the breakdown of what constitutes an urban area is problematic. With growth,
the boundaries of urban areas change over time.
5. Assessment of the Availability of Data from National and International Sources
As indicated above, the percentage urban population can be calculated from censuses, and such data
are available for nearly all countries. Such data are available from national sources (country
publications) as well as from special country questionnaires sent to national statistical offices from the
Statistical Division, DESIPA. The United Nations recommends that countries take censuses every 10
years and these data can be used to calculate the percentage urban. The Population Division, DESIPA
prepares the official United Nations population estimates and projections of percentage urban. Past,
current and projected percentage urban are prepared for all countries by the Population Division,
DESIPA and appear in the United Nations publication, World Urbanization Prospects: The 1994
Revision (see section 7 below).
6. Agencies Involved in the Development of the Indicator
The lead organization is the United Nations Department for Economic and Social Information and Policy
Analysis (DESIPA). The contact point is the Director, Population Division, DESIPA; fax no. (1 211) 963
2147.
7. Further Information
DESIPA. World Urbanization Prospects: The 1994 Revision. Population Division. United Nations Sales
No. E.95.XIII.12. New York, 1995.
DESIPA. 1993 Demographic Yearbook. Statistical Division. United Nations Sales No.E/F.95.XIII.1.
1995.
AREA AND POPULATION OF URBAN FORMAL AND INFORMAL SETTLEMENTS
Social
Chapter 7
State
1. Indicator:
(a)
Name:
Area
and
population
of
urban
formal
and
informal
settlements.
(b) Brief Definition: Urban residential area in square kilometres occupied by formal and informal
settlements,
and
the
number
of
their
occupants.
(c) Measurement Unit: Area: km2; number of occupants.
2. Placement in the Framework
(a) Agenda 21:
(b) Type: State.
Chapter
7:
Promoting
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: The indicator measures both the sizes of informal urban settlements and the residential
density of both formal and informal settlements. By focusing on the legality of human settlements, this
indicator measures the marginality of human living conditions.
(b) Relevance to Sustainable/Unsustainable Development: Settlements characterized by illegality of
tenure and unauthorized shelter are generally marginal and precarious, and do not cater for basic
human needs such as affordable housing. They affect sustainable human settlements development,
human health, and socioeconomic development.
Illegal dwellers generally live in an unsafe and precarious environment, lack basic services, suffer from
the absence of tenure security, and have no legal claim in case of eviction. Also, numerous illegal
settlements are established on lands which are predisposed to natural disasters. Informal settlements
have usually a much higher population density than formal settlements and these living conditions
constitute a threat to human health.
(c) Linkages with Other Indicators: This indicator is closely linked with several other socioeconomic
and environmental indicators, such as rate of growth of urban population, human and economic losses
due to natural disasters, access to adequate sanitation, primary health care, infant mortality,
infrastructure expenditure, and land use.
(d) Targets: No international targets have been established for this indicator.
(e) International Conventions and Agreements: Not applicable, see section 3d above.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Informal settlements refer to: i) residential areas where a
group of housing units has been constructed on land to which the occupant have no legal claim, or
which they occupy illegally; ii) unplanned settlements and areas where housing is not in compliance with
current planning and building regulations (unauthorized housing). Formal settlements refer to land
zoned residential in city master plans or occupied by formal housing.
(b) Measurement Methods: Households and population living in informal settlements are generally
measured in censuses. Area of informal settlements can be evaluated through aerial photography or
land use maps. This indicator should not cover dwelling units which have been regularized, that is those
units for which land titles, leases or occupancy permits have been granted. It should only include those
units which presently occupy land illegally and/or housing units which are not in compliance with current
regulation. Where feasible, the interpretation and meaning of this indicator would be supported by the
comparison of informal settlement area and population to total urban area and population.
(c) The Indicator in the DSR Framework: This is a state indicator, reflecting the major consequence of
unplanned and unsustainable population growth in human settlements.
(d) Limitations of the Indicator: The ephemeral nature and lack of an acceptable operational definition
for this indicator, limit its usefulness, especially for trend analysis. The legal framework for settlements
on which this indicator is based varies from country to country. Informal housing is not registered in
official statistics, any measure of informal settlements remains limited. Information may be obtained from
specific research studies, but it difficult to obtain and may be of variable quality. Homelessness, which is
one of the extreme symptoms of human settlements inadequacy, is not accounted for by this indicator
and in fact the existence of illegal settlements may reduce the incidence of homelessness. This indicator
does not cover informal settlements in rural areas.
(e) Alternative Definitions: Many concepts intended to measure marginality of human settlements
have been formulated: unplanned, squatter, marginal settlements, unconventional, non permanent
structures, housing in compliance, inadequate housing, slums, etc. "Unconventional dwellings" is one of
the most common measures, defined by the number of housing units occupied by households, but
considered inappropriate to human habitation. The type of building (permanent, semi-permanent, non
permanent) which describe the building structures in which households live is another common
measure, but the criteria widely vary from country to country. Alternatively, attempts could be made to
include informal rural settlements within the indicator concept. This would be more comprehensive, but
detract from its urban focus.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Area and population of informal settlements.
(b) Data Availability: These data are more likely to be available at the city level and are generally
collected in large cities affected by informal settlements. Data sets at the national level will only occur
sporadically.
(c) Data Sources: Data from research studies, census data, and aerial photographs.
6. Agencies Involved in the Development of the Indicator
The lead agency is the United Nation Centre for Human Settlements (Habitat). The contact point is the
Director, Programme Coordination, Habitat; fax no. (254 2) 624 266.
7. Further Information
World Bank. Housing: Enabling Markets to Work. A World Bank Policy Paper. The World Bank,
Washington D.C., 1993.
UNCHS (Habitat) and The World Bank. The Housing Indicators Programme. Report of the Executive
Director (Volume I). UNCHS, Nairobi, 1993.
UNCHS (Habitat). Monitoring the Shelter Sector. Housing Indicators Review. UNCHS, Nairobi, 1995.
FLOOR AREA PER PERSON
Social
Chapter 7
State
1. Indicator
(a)
Name:
(b) Brief Definition:
(c) Measurement Unit: m
Defined
Floor
as the
median
area
usable
living
per
space
per
person
person.
2. Placement in the Framework
(a) Agenda 21:
(b) Type: State.
Chapter
7:
Promoting
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: This is a key indicator of housing quality, which measures the adequacy of living space in
dwellings. A low value for the indicator is a sign of overcrowding.
(b) Relevance to Sustainable/Unsustainable Development: This is a key indicator measuring the
adequacy of the basic human need for shelter. Human settlement conditions in many parts of the world
are deteriorating mainly as a result of a low level of investment, although such investment has been
shown to generate considerable public and private sector investment. Housing policies, particularly in
urban areas, greatly affect the living conditions of people. In low income settlements, reduced space per
person can be associated with certain categories of health risks.
(c) Linkages to Other Indicators: This indicator is closely linked to several other socioeconomic
indicators with which it should be considered, including population density, rate of growth of urban
population, area and population of informal settlements, and infrastructure expenditure per capita.
(d) Targets: No targets have been developed for this indicator.
(e) International Conventions and Agreements: This indicator is one of ten "key" housing indicators
approved by the Commission on Human Settlements (Resolution 14/13), to be collected in all countries
and in a number of cities in each country, to measure progress towards meeting the objectives of the
Global Shelter Strategy. Countries are to use the indicators to provide the basis for their country reports
to the Second United Nations Conference on Human Settlements.
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: The floor area should include all living space, along with
bathrooms, internal corridors and closets. Covered semi-private spaces such as corridors, inner
courtyards or verandas should be included in the calculation if used by the household for cooking,
eating, sleeping, or other domestic activities. Floor area refers to a housing unit, defined as a separate
and independent place of abode intended for habitation by one household at the time of the census or
other inquiry.
(b) Measurement Methods: The median floor area of a unit should be divided by the average
household size. If data from household surveys or from a recent census are available, these can be
used. In the absence of better data, the floor area of the median priced dwelling may be used as an
approximation, although this may not be an accurate estimate. If the median cannot be estimated, then
the average should be provided.
(c) The indicator in the DSR Framework: This indicator is a measure of housing quality, an outcome
of housing demand and housing supply, determined by the overall housing policy framework. As such,
this indicator is a State measure in the DSR Framework.
(d) Limitations of the Indicator: Results for this indicator may vary considerably if collected at the city,
national, urban/rural levels, given the variations in land availability and types of human settlements and
activities. Informal settlements in particular are likely to have much less space per person, as are
disadvantaged groups. Various levels of data collection are necessary to provide a full picture of this
specific housing outcome. Housing size and housing quality are usually but not necessarily linked, and
floor area per person may not give a complete picture of living conditions. Cultural values affect
sensitivity to crowding. For these reasons, interpretation of this indicator is difficult, and should be
completed in conjunction with related indicators (see section 3c above).
(e) Alternative Definitions: Alternative measures of crowding have been the subject of data collection
and reporting in international statistical compendia. The two most common are persons per room and
households per dwelling unit, each of which was included among data collected during the first phase of
the Housing Indicators Programme (UNCHS, World Bank, 1992). Surveys have shown that floor area
per person is more precise and policy-sensitive than the other two indicators. Habitat, the United
Nations Centre for Human Settlements (UNCHS) has developed and tested a series of crowding
indicators in low-income settlements. They include, among others, percentage of housing units with
more than one household, in-house living area per person, percentage of housing units with more than
three persons per room, number of households per building and per housing unit, number of persons
per building.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Median floor area of housing units; average number of
persons per household.
(b) Data Availability: The data are generally available at the country level. This indicator was collected
in 52 countries (one city per country) by the Shelter Sector Performance Indicators Programme in 1992
(UNCHS, World Bank). It is being collected worldwide by the UNCHS Indicators Programme in
preparation for the Habitat II Conference. A detailed set of crowding indicators has been developed and
the data collected for Jakarta (Indonesia), Bissau (Guinea Bissau), and Accra (Ghana).
(c) Data Sources: Primary data sources include censuses or household surveys. The indicator is
reported in the Housing Indicators Programme report listed in section 7 below.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the United Nations Centre for Human Settlements (Habitat). The
contact point is the Director, Programme Coordination, UNCHS; fax no. (254 2) 624 266.
(b) Other Organizations: The World Bank.
7. Further Information
World Bank. Housing: Enabling Markets to Work. The World Bank, Washington D.C., 1993 (A World
Bank Policy Paper).
UNCHS (Habitat), World Bank. The Housing Indicators Programme. Report of the Executive Director
(Volume I). UNCHS, Nairobi, 1993.
UNCHS (Habitat). Monitoring the Shelter Sector. Housing Indicators Review. UNCHS, Nairobi, 1995.
UNCHS (Habitat). Human Settlement, Interventions Addressing Crowding and Health Issues, UNCHS,
Nairobi, 1995.
HOUSE PRICE TO INCOME RATIO
Social
Chapter 7
State
1. Indicator
(a)
Name:
House
price
to
income
ratio.
(b) Brief Definition: This indicator is defined as the ratio of the median free-market price of a dwelling
unit
and
the
median
annual
household
income.
(c) Unit of Measurement: Ratio
2. Placement in the Framework
(a) Agenda 21: Chapter
(b) Type of Indicator: State
7:
Promoting
Sustainable
Human
Settlement
Development.
3. Significance (Policy Relevance)
(a) Purpose: This indicator is a key measure of housing affordability, providing information on the
overall performance of housing markets and important insights into several housing market
dysfunctions, indicative of a variety of policy failures.
(b) Relevance to Sustainable/Unsustainable Development: This is a key indicator measuring human
settlements sustainability by determining housing affordability, and therefore the impact of market forces
and housing policies on the living conditions of people. It is strongly influenced by government land use
policy and is particularly relevant to urban areas.
(c) Linkages to Other Indicators: There are close links between this indicator and a number of other
socioeconomic Driving Force and Response measures. These would include: infrastructure expenditure
per capita, percent of population in urban areas, increase in urban population, population density, area
and population of informal settlements.
(d) Targets: International agreements have not established specific national and global goals for this
indicator.
(e) International Conventions and Agreements: This indicator is one of ten "key" housing indicators
approved by the Commission on Human Settlements (Resolution 14/13), to be collected in all countries
and in a number of cities in each country, to measure progress towards meeting the objectives of the
Global Shelter Strategy. Countries are to use the indicators to provide the basis for their country reports
for the Second United Nations Conference on Human Settlements (Habitat II).
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Two intermediate measures are required: median house
price and median annual household income.
i) Median household income: Household income is defined as gross income from all sources, including
wages, salaries, incomes from businesses or informal sector activities, investment income, and, where
information is available, income in kind such as consumption of agricultural product which might have
been sold.
ii) Median house price: The median-priced house is that house which has 50% of the houses priced
below it, and 50% of the houses priced above it. Housing value is defined as the price at which a house
would be sold if placed on the market for a reasonable length of time by a seller who is not under
pressure to sell.
(b) Measurement Methods: The following methods for calculating household incomes and the median
price house are suggested.
Many countries may have recent household surveys containing information on median household
incomes or expenditures which can be used directly. Expenditures data rather than incomes data may
be used to estimate incomes if these data are more readily available. In fact, for lower income earners
or where incomes are routinely concealed, expenditures may be a better measure of income than
reported incomes. Mean household incomes, although less preferable, are often easier to obtain as a
recent estimate (for example, by dividing household income or household expenditure in the National
Accounts by the number of households).
If a survey is available, which has mean and median incomes, but which is too old to yield good
estimates of household income, the ratio of median to mean incomes may still be used to obtain a new
median, because the distribution of incomes does not change as rapidly as incomes themselves.
The calculation of the price of the median-priced house should, include all housing, both new and old,
and both formal and informal. If, for example, the majority of the housing stock is informal, and the
informal housing stock is generally cheaper than the formal housing stock, then the median priced
house will probably be an informal unit. For blocks of apartments or multiple-family dwellings which are
usually sold as a single building, the value of one dwelling unit should be estimated as a pro rata share
of the total sale price. This is particularly relevant for countries in Africa where the majority of housing is
of this type.
The following methods are available for estimating the median price.
i) Method 1: Where the informal sector is small and data is reliable, median house price can be
determined directly from published (formal) sales figures or from recent surveys.
ii) Method 2: If recent average prices are available, they can be converted to median price by using a
median/mean ratio from an older household survey. In much of the research done on housing markets
in developing countries, it has been found that median prices are generally about 70% of the average.
This figure is higher when housing is more equally distributed and lower when housing is more
unequally distributed.
iii) Method 3: If no direct data are available, then prices need to be estimated for each sub-market.
Estimate the percentage of all housing units and price range per unit. The median should then be
estimated, using a graph, representing the different sub-markets. In some cases, the price ranges of
several different kinds of dwellings may overlap around the median, so that the median dwelling could
be of either type.
(c) The Indicator in the DSR Framework: This indicator is a measure of housing affordability, result of
housing demand and housing supply, determined by the overall housing policy framework. As such, this
indicator represents a State measure in the DSR Framework.
(d) Limitations of the Indicator: Results for this indicator may vary considerably if collected at the city,
national, urban/rural levels, given the variations in land availability and type of human settlements and
activities. Although median house price is more indicative of general housing affordability than mean
price, some population subgroups may find housing much less affordable than the median. Also,
although rents generally reflect house prices, rents may be much more or less affordable than this
indicator would show, depending on rental market regulation and the availability of rental housing.
Various levels of data collection are necessary to provide a full picture of housing affordability. In some
countries such as China, no formal housing market exists and a meaningful value for the indicator is
difficult to estimate.
The influence of the financial markets are not reflected by this indicator. It is a measure of what the
market will pay, rather than a measure of the cost to build housing.
(e) Alternative Indicator Definitions: Another key and complementary measure of housing affordability
is the rent-to-income ratio, defined as the ratio of the median annual rent of a dwelling unit and the
median household income of renters. It may be very relevant in some countries and cities where rental
housing is a common tenure type.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Median household income; median-priced house.
(b) Data Availability: Reliable data are generally available for many countries. Median household
income can be extracted from household surveys and the median-priced house estimated based on
market research. Such estimates from respondents correspond closely to actual market values. This
indicator has been collected in 53 countries (one city per country) by the Shelter Sector Performance
Indicators Programme in 1992 (UNCHS, World Bank). It is being collected worldwide by the United
Nations Centre for Human Settlements (UNCHS) Indicators Programme in preparation for the Habitat II
Conference.
(c) Data Sources: Primary data sources exist at the individual urban area. This indicator is reported in
the Housing Indicators Programme report listed in section 7 below.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the United Nations Centre for Human Settlements (Habitat). The
contact point is the Director, Programme Coordination, UNCHS; fax no. (254 2) 624 266.
(b) Other Organizations: The World Bank
7. Further Information
World Bank. Housing: Enabling Markets to Work. A World Bank Policy Paper. Washington D.C., 1993.
UNCHS (Habitat), World Bank. The Housing Indicators Programme. Report of the Executive Director
(Volume I). UNCHS, Nairobi, 1993.
UNCHS (Habitat). Monitoring the Shelter Sector. Housing Indicators Review. UNCHS, Nairobi, 1995.
INFRASTRUCTURE EXPENDITURE PER CAPITA
Social
Chapter 7
Response
1. Indicator
(a)
Name:
Infrastructure
expenditure
per
capita.
(b) Brief Definition: This indicator is defined as the per capita expenditure in US dollars by all levels of
government, including government-owned companies and utilities, on urban infrastructure services
during
the
current
year.
(c) Measurement Unit: $US
2. Placement in the Framework
(a) Agenda 21: Chapter 7:
(b) Type of Indicator: Response
3. Significance (Policy Relevance)
Promoting
Sustainable
Human
Settlement
Development
(a) Purpose: This indicator measures the involvement of the different levels of the government and the
private sector in the provision, improvement and maintenance of infrastructure. As such, it is a key
measure of provision of basic services, including housing to the population.
(b) Relevance to Sustainable/Unsustainable Development: Infrastructure is a major indicator for the
monitoring of the Global Shelter Strategy to the Year 2000, which calls for a fundamental shift in
government's role in housing from attempting to provide housing directly towards an enabling role, one
which facilitates, energises and supports the activities of the private sector, both formal and informal.
The enabling strategy provides the basis for a sustainable long term approach to human settlement
management.
Total infrastructure expenditure interacts strongly with new land development and construction, and also
with improved access to services by households. Low levels of infrastructure expenditures result in land
supply bottlenecks and thus in higher prices for land and housing. They also result in inadequate
provision of residential amenities, such as water, sewerage, drainage, electricity, and transportation
facilities all of which can affect the quality and access to housing.
(c) Linkages to Other Indicators: Infrastructure development energizes the shelter sector, and
improves housing affordability. It is closely linked with other socioeconomic and environment indicators,
especially those associated with human settlements, including house price-to-income ratio, land use
change, transport fuel consumption, land and area of informal settlements, access to adequate
sanitation, and infant mortality rate.
(d) Targets: International agreements have not established specific national and global goals for this
indicator.
(e) International Conventions and Agreements: This indicator is one of ten "key" housing indicators
approved by the Commission on Human Settlements (Resolution 14/13), to be collected in all countries
and in a number of cities in each country, to measure progress towards meeting the objectives of the
Global Shelter Strategy. Countries are to use the indicators to provide the basis for their country reports
for the Second United Nations Conference on Human Settlements (Habitat II).
4. Methodological Description and Underlying Definitions
(a) Underlying Definitions and Concepts: Infrastructure includes operations, maintenance, and capital
expenditures on physical infrastructure such as urban roads, railways, sewerage, drainage, water
supply, electricity, and garbage collection, but not social infrastructure such as health and education
expenditure.
(b) Measurement Methods: Infrastructure expenditures are comprised of three major components,
capital expenditures (construction costs), recurrent expenditures (operations, maintenance, salaries,
etc.), and capital servicing (debt service and depreciation). If there were unusually high capital
expenditures during the last year for which figures are available, then they should not be included in the
indicator. Only their first year depreciation should be considered as current year expenditure. Only real
outlays or real transfers should be counted as expenditure. If debts (for example, to the central
government) are not actually paid, or depreciation payments are not actually transferred to a sinking
fund, they should not be counted as expenditures.
(c) The indicator in the DSR Framework: Infrastructure expenditure is a key measure of human
settlement management, as infrastructure constitutes the main input for land and shelter development
and improvement. It is a major Response to inadequate land development, and therefore housing
production, in order to meet the increasing demand of populations.
(d) Limitations of the Indicator: The methodology for this indicator requires more work in, for example,
defining the scope of infrastructure to be included, and in the treatment of interest payments and
depreciation. The interpretation and meaning of this indicator will vary greatly by country and geographic
region.
In many countries, infrastructure expenditure is targeted towards certain areas of the city and specific
groups of the population. Aggregated data for the city will not show who are the real beneficiaries of
infrastructure expenditure. Also, sectoral expenditures on different categories of infrastructure may have
very different outcomes for sustainability.
(e) Alternative Indicator Definitions: Under the limitations discussed above, it may be advisable to
consider a more basic definition of infrastructure to include, for example, water supply, sewerage
collection and treatment, roads, communication, and schools. This, however, would increase the overlap
with other existing, more disaggregated indicators, such as water and sanitation services.
5. Assessment of the Availability of Data from National and International Sources
(a) Data Needed to Compile the Indicator: Three data components are required: capital expenditures
(construction costs), recurrent expenditures (operations, maintenance, salaries, etc.), capital servicing
(debt service and depreciation).
(b) Data Availability: This indicator has been collected in 44 countries (one city per country) by the
Shelter Sector Performance Indicators Programme in 1992 (UNCHS, World Bank). It is being collected
worldwide by the United Nations Centre for Human Settlements (UNCHS) Indicators Programme in
preparation for the Habitat II Conference.
(c) Data Sources: This indicator is obtained from expenditure accounts of local and central
governments, and from major public agencies. International data is available from the Housing
Indicators Programme report listed in section 7 below.
6. Agencies Involved in the Development of the Indicator
(a) Lead Agency: The lead agency is the United Nations Centre for Human Settlements (Habitat). The
contact point is the Director, Programme Coordination, UNCHS; fax no. (254 2) 624 266.
(b) Other Organizations: The World Bank.
7. Further Information
World Bank. Housing: Enabling Markets to Work. A World Bank Policy Paper. Washington D.C., 1993.
UNCHS (Habitat), World Bank. The Housing Indicators Programme. Report of the Executive Director
(Volume I). UNCHS, Nairobi, 1993.
UNCHS (Habitat). Monitoring the Shelter Sector. Housing Indicators Review. UNCHS, Nairobi, 1995.
i
United Nations Agenda 21: http://www.un.org/esa/sustdev/agenda21.htm
Census Of Malta 1995 Web-Mapping: http://CensusofMalta1995
iii
Internal Migration Report 1996, Planning Authority, unpublished
iv
Census of Malta, 1995, Central Office of Statistics, 1995
v
Demography Topic Paper May 2001, Malta Planning Authority
vi
ibid
vii
ibid
viii
OECD: http://www.oecd.org/
ix
Blue Plan, October 2000, 130 indicators for sustainable development in the Mediterranean region
x
UN Sustainable Development: http://www.un.org/esa/sustdev/indisd/english/introduc.htm
ii